Overview

Dataset statistics

Number of variables62
Number of observations176
Missing cells4202
Missing cells (%)38.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory85.4 KiB
Average record size in memory496.7 B

Variable types

Numeric13
Categorical40
Unsupported9

Alerts

airdate has constant value "2020-12-04" Constant
_embedded.show.dvdCountry.name has constant value "Russian Federation" Constant
_embedded.show.dvdCountry.code has constant value "RU" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Kamchatka" Constant
url has a high cardinality: 176 distinct values High cardinality
name has a high cardinality: 160 distinct values High cardinality
summary has a high cardinality: 88 distinct values High cardinality
_links.self.href has a high cardinality: 176 distinct values High cardinality
_embedded.show.url has a high cardinality: 91 distinct values High cardinality
_embedded.show.name has a high cardinality: 91 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 66 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 83 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 86 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 86 distinct values High cardinality
_embedded.show.summary has a high cardinality: 81 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 91 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 91 distinct values High cardinality
image.medium has a high cardinality: 98 distinct values High cardinality
image.original has a high cardinality: 98 distinct values High cardinality
id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
season is highly correlated with rating.average and 3 other fieldsHigh correlation
number is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 3 other fieldsHigh correlation
id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
season is highly correlated with number and 7 other fieldsHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with season and 4 other fieldsHigh correlation
rating.average is highly correlated with season and 7 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 3 other fieldsHigh correlation
id is highly correlated with _embedded.show.externals.tvrageHigh correlation
season is highly correlated with rating.average and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.externals.tvrageHigh correlation
_embedded.show.network.id is highly correlated with number and 1 other fieldsHigh correlation
id is highly correlated with number and 34 other fieldsHigh correlation
season is highly correlated with number and 28 other fieldsHigh correlation
number is highly correlated with id and 35 other fieldsHigh correlation
type is highly correlated with summary and 12 other fieldsHigh correlation
airtime is highly correlated with season and 33 other fieldsHigh correlation
airstamp is highly correlated with id and 41 other fieldsHigh correlation
runtime is highly correlated with season and 37 other fieldsHigh correlation
summary is highly correlated with id and 43 other fieldsHigh correlation
rating.average is highly correlated with airstamp and 26 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.status is highly correlated with airstamp and 32 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 35 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 37 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.weight is highly correlated with airstamp and 35 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 39 other fieldsHigh correlation
image.medium is highly correlated with id and 42 other fieldsHigh correlation
image.original is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 36 other fieldsHigh correlation
number has 5 (2.8%) missing values Missing
runtime has 6 (3.4%) missing values Missing
image has 176 (100.0%) missing values Missing
summary has 88 (50.0%) missing values Missing
rating.average has 146 (83.0%) missing values Missing
_embedded.show.runtime has 96 (54.5%) missing values Missing
_embedded.show.averageRuntime has 3 (1.7%) missing values Missing
_embedded.show.ended has 129 (73.3%) missing values Missing
_embedded.show.officialSite has 17 (9.7%) missing values Missing
_embedded.show.rating.average has 124 (70.5%) missing values Missing
_embedded.show.network has 176 (100.0%) missing values Missing
_embedded.show.webChannel.id has 5 (2.8%) missing values Missing
_embedded.show.webChannel.name has 5 (2.8%) missing values Missing
_embedded.show.webChannel.country has 176 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 50 (28.4%) missing values Missing
_embedded.show.dvdCountry has 176 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 173 (98.3%) missing values Missing
_embedded.show.externals.thetvdb has 49 (27.8%) missing values Missing
_embedded.show.externals.imdb has 73 (41.5%) missing values Missing
_embedded.show.image.medium has 8 (4.5%) missing values Missing
_embedded.show.image.original has 8 (4.5%) missing values Missing
_embedded.show.summary has 10 (5.7%) missing values Missing
_embedded.show.webChannel.country.name has 103 (58.5%) missing values Missing
_embedded.show.webChannel.country.code has 103 (58.5%) missing values Missing
_embedded.show.webChannel.country.timezone has 103 (58.5%) missing values Missing
image.medium has 78 (44.3%) missing values Missing
image.original has 78 (44.3%) missing values Missing
_embedded.show._links.nextepisode.href has 160 (90.9%) missing values Missing
_embedded.show.network.id has 165 (93.8%) missing values Missing
_embedded.show.network.name has 165 (93.8%) missing values Missing
_embedded.show.network.country.name has 165 (93.8%) missing values Missing
_embedded.show.network.country.code has 165 (93.8%) missing values Missing
_embedded.show.network.country.timezone has 165 (93.8%) missing values Missing
_embedded.show.network.officialSite has 176 (100.0%) missing values Missing
_embedded.show.webChannel has 176 (100.0%) missing values Missing
_embedded.show.image has 176 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 175 (99.4%) missing values Missing
_embedded.show.dvdCountry.code has 175 (99.4%) missing values Missing
_embedded.show.dvdCountry.timezone has 175 (99.4%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:37:03.801236
Analysis finished2022-09-06 02:37:26.560922
Duration22.76 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001147.943
Minimum1910446
Maximum2341524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:26.633475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1910446
5-th percentile1937861
Q11969234.5
median1977645
Q31984194.75
95-th percentile2236970.25
Maximum2341524
Range431078
Interquartile range (IQR)14960.25

Descriptive statistics

Standard deviation83717.22656
Coefficient of variation (CV)0.04183460141
Kurtosis6.664312989
Mean2001147.943
Median Absolute Deviation (MAD)7921.5
Skewness2.701366277
Sum352202038
Variance7008574023
MonotonicityNot monotonic
2022-09-05T21:37:26.752277image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19840161
 
0.6%
19610031
 
0.6%
19697241
 
0.6%
19763361
 
0.6%
19766611
 
0.6%
19740811
 
0.6%
19748181
 
0.6%
22460781
 
0.6%
19766441
 
0.6%
19792351
 
0.6%
Other values (166)166
94.3%
ValueCountFrequency (%)
19104461
0.6%
19200591
0.6%
19200601
0.6%
19200611
0.6%
19200621
0.6%
19200631
0.6%
19200641
0.6%
19248881
0.6%
19313301
0.6%
19400381
0.6%
ValueCountFrequency (%)
23415241
0.6%
23277951
0.6%
23088311
0.6%
23088301
0.6%
23088291
0.6%
22986591
0.6%
22460781
0.6%
22369721
0.6%
22369711
0.6%
22369701
0.6%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
https://www.tvmaze.com/episodes/1984016/roast-battle-labelcom-1x14-14-anton-sastun
 
1
https://www.tvmaze.com/episodes/1961003/cuma-2x06-seria-12
 
1
https://www.tvmaze.com/episodes/1969724/kings-of-joburg-1x06-the-sacrifice
 
1
https://www.tvmaze.com/episodes/1976336/fjols-til-fjells-1x03-stamp-og-familieforokelse
 
1
https://www.tvmaze.com/episodes/1976661/influencers-1x03-beating-hearts
 
1
Other values (171)
171 

Length

Max length174
Median length97.5
Mean length78.20454545
Min length58

Characters and Unicode

Total characters13764
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1984016/roast-battle-labelcom-1x14-14-anton-sastun
2nd rowhttps://www.tvmaze.com/episodes/1961003/cuma-2x06-seria-12
3rd rowhttps://www.tvmaze.com/episodes/1976570/zakon-i-besporyadok-1x03-seria-3
4th rowhttps://www.tvmaze.com/episodes/1976571/zakon-i-besporyadok-1x04-seria-4
5th rowhttps://www.tvmaze.com/episodes/1979225/kotiki-1x05-seria-5

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1984016/roast-battle-labelcom-1x14-14-anton-sastun1
 
0.6%
https://www.tvmaze.com/episodes/1961003/cuma-2x06-seria-121
 
0.6%
https://www.tvmaze.com/episodes/1969724/kings-of-joburg-1x06-the-sacrifice1
 
0.6%
https://www.tvmaze.com/episodes/1976336/fjols-til-fjells-1x03-stamp-og-familieforokelse1
 
0.6%
https://www.tvmaze.com/episodes/1976661/influencers-1x03-beating-hearts1
 
0.6%
https://www.tvmaze.com/episodes/1974081/wish-you-1x01-episode-11
 
0.6%
https://www.tvmaze.com/episodes/1974818/wish-you-1x02-episode-21
 
0.6%
https://www.tvmaze.com/episodes/2246078/wish-you-s01-special-wish-you-talk-live-episode-11
 
0.6%
https://www.tvmaze.com/episodes/1976644/bhaag-beanie-bhaag-1x01-episode-11
 
0.6%
https://www.tvmaze.com/episodes/1979235/bhaag-beanie-bhaag-1x02-episode-21
 
0.6%
Other values (166)166
94.3%

Length

2022-09-05T21:37:26.874919image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1984016/roast-battle-labelcom-1x14-14-anton-sastun1
 
0.6%
https://www.tvmaze.com/episodes/1961003/cuma-2x06-seria-121
 
0.6%
https://www.tvmaze.com/episodes/1983280/forstegangstjenesten-s01-special-bloopers1
 
0.6%
https://www.tvmaze.com/episodes/1976570/zakon-i-besporyadok-1x03-seria-31
 
0.6%
https://www.tvmaze.com/episodes/1976571/zakon-i-besporyadok-1x04-seria-41
 
0.6%
https://www.tvmaze.com/episodes/1979225/kotiki-1x05-seria-51
 
0.6%
https://www.tvmaze.com/episodes/1972557/the-wolf-1x15-episode-151
 
0.6%
https://www.tvmaze.com/episodes/1972558/the-wolf-1x16-episode-161
 
0.6%
https://www.tvmaze.com/episodes/1910446/the-founder-of-diabolism-q-1x20-drunkenness1
 
0.6%
https://www.tvmaze.com/episodes/2082172/ling-jian-zun-4x29-di129ji1
 
0.6%
Other values (166)166
94.3%

Most occurring characters

ValueCountFrequency (%)
e1163
 
8.4%
-1036
 
7.5%
/880
 
6.4%
s861
 
6.3%
t860
 
6.2%
o727
 
5.3%
w593
 
4.3%
a573
 
4.2%
i543
 
3.9%
p478
 
3.5%
Other values (30)6050
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9422
68.5%
Decimal Number1898
 
13.8%
Other Punctuation1408
 
10.2%
Dash Punctuation1036
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1163
12.3%
s861
 
9.1%
t860
 
9.1%
o727
 
7.7%
w593
 
6.3%
a573
 
6.1%
i543
 
5.8%
p478
 
5.1%
m473
 
5.0%
d384
 
4.1%
Other values (16)2767
29.4%
Decimal Number
ValueCountFrequency (%)
1417
22.0%
0262
13.8%
9254
13.4%
2203
10.7%
7165
 
8.7%
4128
 
6.7%
6126
 
6.6%
8124
 
6.5%
3117
 
6.2%
5102
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/880
62.5%
.352
 
25.0%
:176
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-1036
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9422
68.5%
Common4342
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1163
12.3%
s861
 
9.1%
t860
 
9.1%
o727
 
7.7%
w593
 
6.3%
a573
 
6.1%
i543
 
5.8%
p478
 
5.1%
m473
 
5.0%
d384
 
4.1%
Other values (16)2767
29.4%
Common
ValueCountFrequency (%)
-1036
23.9%
/880
20.3%
1417
9.6%
.352
 
8.1%
0262
 
6.0%
9254
 
5.8%
2203
 
4.7%
:176
 
4.1%
7165
 
3.8%
4128
 
2.9%
Other values (4)469
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII13764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1163
 
8.4%
-1036
 
7.5%
/880
 
6.4%
s861
 
6.3%
t860
 
6.2%
o727
 
5.3%
w593
 
4.3%
a573
 
4.2%
i543
 
3.9%
p478
 
3.5%
Other values (30)6050
44.0%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct160
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Episode 1
 
5
Episode 6
 
4
Episode 2
 
4
Episode 3
 
3
Episode 5
 
3
Other values (155)
157 

Length

Max length99
Median length58
Mean length16.47727273
Min length3

Characters and Unicode

Total characters2900
Distinct characters129
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)87.5%

Sample

1st row#14 - Антон Шастун
2nd rowСерия 12
3rd rowСерия 3
4th rowСерия 4
5th rowСерия 5

Common Values

ValueCountFrequency (%)
Episode 15
 
2.8%
Episode 64
 
2.3%
Episode 24
 
2.3%
Episode 33
 
1.7%
Episode 53
 
1.7%
Episode 43
 
1.7%
#14 - Антон Шастун1
 
0.6%
We Are Brothers1
 
0.6%
The Heart of the Knights1
 
0.6%
Vader (Father)1
 
0.6%
Other values (150)150
85.2%

Length

2022-09-05T21:37:26.998648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode34
 
6.5%
the31
 
5.9%
14
 
2.7%
19
 
1.7%
folge8
 
1.5%
37
 
1.3%
of7
 
1.3%
57
 
1.3%
46
 
1.1%
in6
 
1.1%
Other values (334)398
75.5%

Most occurring characters

ValueCountFrequency (%)
351
 
12.1%
e265
 
9.1%
o167
 
5.8%
i162
 
5.6%
s132
 
4.6%
r130
 
4.5%
a129
 
4.4%
t110
 
3.8%
n100
 
3.4%
d92
 
3.2%
Other values (119)1262
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1915
66.0%
Uppercase Letter457
 
15.8%
Space Separator351
 
12.1%
Decimal Number101
 
3.5%
Other Punctuation51
 
1.8%
Dash Punctuation17
 
0.6%
Open Punctuation2
 
0.1%
Math Symbol2
 
0.1%
Close Punctuation2
 
0.1%
Other Letter2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e265
13.8%
o167
 
8.7%
i162
 
8.5%
s132
 
6.9%
r130
 
6.8%
a129
 
6.7%
t110
 
5.7%
n100
 
5.2%
d92
 
4.8%
l78
 
4.1%
Other values (47)550
28.7%
Uppercase Letter
ValueCountFrequency (%)
E48
 
10.5%
T39
 
8.5%
F28
 
6.1%
S24
 
5.3%
A24
 
5.3%
W23
 
5.0%
L21
 
4.6%
B21
 
4.6%
P21
 
4.6%
C20
 
4.4%
Other values (35)188
41.1%
Decimal Number
ValueCountFrequency (%)
125
24.8%
218
17.8%
311
10.9%
59
 
8.9%
49
 
8.9%
67
 
6.9%
07
 
6.9%
96
 
5.9%
85
 
5.0%
74
 
4.0%
Other Punctuation
ValueCountFrequency (%)
,11
21.6%
.8
15.7%
/8
15.7%
'7
13.7%
#5
9.8%
:5
9.8%
?3
 
5.9%
"2
 
3.9%
!1
 
2.0%
&1
 
2.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
351
100.0%
Dash Punctuation
ValueCountFrequency (%)
-17
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2220
76.6%
Common526
 
18.1%
Cyrillic152
 
5.2%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e265
 
11.9%
o167
 
7.5%
i162
 
7.3%
s132
 
5.9%
r130
 
5.9%
a129
 
5.8%
t110
 
5.0%
n100
 
4.5%
d92
 
4.1%
l78
 
3.5%
Other values (47)855
38.5%
Cyrillic
ValueCountFrequency (%)
и15
 
9.9%
е12
 
7.9%
а11
 
7.2%
р11
 
7.2%
А7
 
4.6%
я7
 
4.6%
С7
 
4.6%
к7
 
4.6%
у6
 
3.9%
с6
 
3.9%
Other values (35)63
41.4%
Common
ValueCountFrequency (%)
351
66.7%
125
 
4.8%
218
 
3.4%
-17
 
3.2%
,11
 
2.1%
311
 
2.1%
59
 
1.7%
49
 
1.7%
.8
 
1.5%
/8
 
1.5%
Other values (15)59
 
11.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2736
94.3%
Cyrillic152
 
5.2%
None10
 
0.3%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
351
 
12.8%
e265
 
9.7%
o167
 
6.1%
i162
 
5.9%
s132
 
4.8%
r130
 
4.8%
a129
 
4.7%
t110
 
4.0%
n100
 
3.7%
d92
 
3.4%
Other values (65)1098
40.1%
Cyrillic
ValueCountFrequency (%)
и15
 
9.9%
е12
 
7.9%
а11
 
7.2%
р11
 
7.2%
А7
 
4.6%
я7
 
4.6%
С7
 
4.6%
к7
 
4.6%
у6
 
3.9%
с6
 
3.9%
Other values (35)63
41.4%
None
ValueCountFrequency (%)
ü2
20.0%
ó2
20.0%
ö2
20.0%
í1
10.0%
é1
10.0%
Ş1
10.0%
ø1
10.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.27840909
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:27.088649image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile12.5
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation395.4961684
Coefficient of variation (CV)4.806803786
Kurtosis20.80279827
Mean82.27840909
Median Absolute Deviation (MAD)0
Skewness4.750321528
Sum14481
Variance156417.2192
MonotonicityNot monotonic
2022-09-05T21:37:27.174343image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1122
69.3%
423
 
13.1%
212
 
6.8%
20207
 
4.0%
73
 
1.7%
102
 
1.1%
52
 
1.1%
32
 
1.1%
111
 
0.6%
171
 
0.6%
ValueCountFrequency (%)
1122
69.3%
212
 
6.8%
32
 
1.1%
423
 
13.1%
52
 
1.1%
73
 
1.7%
102
 
1.1%
111
 
0.6%
171
 
0.6%
181
 
0.6%
ValueCountFrequency (%)
20207
 
4.0%
181
 
0.6%
171
 
0.6%
111
 
0.6%
102
 
1.1%
73
 
1.7%
52
 
1.1%
423
13.1%
32
 
1.1%
212
6.8%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct38
Distinct (%)22.2%
Missing5
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean15.20467836
Minimum1
Maximum331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:27.270911image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q310
95-th percentile54
Maximum331
Range330
Interquartile range (IQR)7

Descriptive statistics

Standard deviation39.50814036
Coefficient of variation (CV)2.59842
Kurtosis39.49277414
Mean15.20467836
Median Absolute Deviation (MAD)3
Skewness5.919614739
Sum2600
Variance1560.893154
MonotonicityNot monotonic
2022-09-05T21:37:27.376821image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
121
11.9%
319
10.8%
618
10.2%
216
 
9.1%
415
 
8.5%
515
 
8.5%
89
 
5.1%
77
 
4.0%
97
 
4.0%
134
 
2.3%
Other values (28)40
22.7%
(Missing)5
 
2.8%
ValueCountFrequency (%)
121
11.9%
216
9.1%
319
10.8%
415
8.5%
515
8.5%
618
10.2%
77
 
4.0%
89
5.1%
97
 
4.0%
104
 
2.3%
ValueCountFrequency (%)
3311
0.6%
2901
0.6%
1911
0.6%
1451
0.6%
1081
0.6%
831
0.6%
781
0.6%
601
0.6%
591
0.6%
491
0.6%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
regular
171 
insignificant_special
 
4
significant_special
 
1

Length

Max length21
Median length7
Mean length7.386363636
Min length7

Characters and Unicode

Total characters1300
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular171
97.2%
insignificant_special4
 
2.3%
significant_special1
 
0.6%

Length

2022-09-05T21:37:27.472363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:27.562272image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular171
97.2%
insignificant_special4
 
2.3%
significant_special1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
r342
26.3%
a181
13.9%
e176
13.5%
g176
13.5%
l176
13.5%
u171
13.2%
i24
 
1.8%
n14
 
1.1%
s10
 
0.8%
c10
 
0.8%
Other values (4)20
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1295
99.6%
Connector Punctuation5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r342
26.4%
a181
14.0%
e176
13.6%
g176
13.6%
l176
13.6%
u171
13.2%
i24
 
1.9%
n14
 
1.1%
s10
 
0.8%
c10
 
0.8%
Other values (3)15
 
1.2%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1295
99.6%
Common5
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
r342
26.4%
a181
14.0%
e176
13.6%
g176
13.6%
l176
13.6%
u171
13.2%
i24
 
1.9%
n14
 
1.1%
s10
 
0.8%
c10
 
0.8%
Other values (3)15
 
1.2%
Common
ValueCountFrequency (%)
_5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r342
26.3%
a181
13.9%
e176
13.5%
g176
13.5%
l176
13.5%
u171
13.2%
i24
 
1.8%
n14
 
1.1%
s10
 
0.8%
c10
 
0.8%
Other values (4)20
 
1.5%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2020-12-04
176 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1760
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-04
2nd row2020-12-04
3rd row2020-12-04
4th row2020-12-04
5th row2020-12-04

Common Values

ValueCountFrequency (%)
2020-12-04176
100.0%

Length

2022-09-05T21:37:27.638297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:27.732044image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-04176
100.0%

Most occurring characters

ValueCountFrequency (%)
2528
30.0%
0528
30.0%
-352
20.0%
1176
 
10.0%
4176
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1408
80.0%
Dash Punctuation352
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2528
37.5%
0528
37.5%
1176
 
12.5%
4176
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2528
30.0%
0528
30.0%
-352
20.0%
1176
 
10.0%
4176
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2528
30.0%
0528
30.0%
-352
20.0%
1176
 
10.0%
4176
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
139 
20:00
 
12
12:00
 
5
06:00
 
4
21:00
 
4
Other values (11)
 
12

Length

Max length5
Median length0
Mean length1.051136364
Min length0

Characters and Unicode

Total characters185
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)5.7%

Sample

1st row
2nd row
3rd row12:00
4th row12:00
5th row

Common Values

ValueCountFrequency (%)
139
79.0%
20:0012
 
6.8%
12:005
 
2.8%
06:004
 
2.3%
21:004
 
2.3%
18:002
 
1.1%
18:301
 
0.6%
08:301
 
0.6%
08:451
 
0.6%
09:001
 
0.6%
Other values (6)6
 
3.4%

Length

2022-09-05T21:37:27.856661image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0012
32.4%
12:005
13.5%
06:004
 
10.8%
21:004
 
10.8%
18:002
 
5.4%
18:301
 
2.7%
08:301
 
2.7%
08:451
 
2.7%
09:001
 
2.7%
09:151
 
2.7%
Other values (5)5
13.5%

Most occurring characters

ValueCountFrequency (%)
087
47.0%
:37
20.0%
224
 
13.0%
115
 
8.1%
85
 
2.7%
64
 
2.2%
54
 
2.2%
94
 
2.2%
33
 
1.6%
42
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number148
80.0%
Other Punctuation37
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
087
58.8%
224
 
16.2%
115
 
10.1%
85
 
3.4%
64
 
2.7%
54
 
2.7%
94
 
2.7%
33
 
2.0%
42
 
1.4%
Other Punctuation
ValueCountFrequency (%)
:37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common185
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
087
47.0%
:37
20.0%
224
 
13.0%
115
 
8.1%
85
 
2.7%
64
 
2.2%
54
 
2.2%
94
 
2.2%
33
 
1.6%
42
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
087
47.0%
:37
20.0%
224
 
13.0%
115
 
8.1%
85
 
2.7%
64
 
2.2%
54
 
2.2%
94
 
2.2%
33
 
1.6%
42
 
1.1%

airstamp
Categorical

HIGH CORRELATION

Distinct21
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2020-12-04T12:00:00+00:00
97 
2020-12-04T17:00:00+00:00
23 
2020-12-04T11:00:00+00:00
22 
2020-12-04T00:00:00+00:00
 
5
2020-12-04T04:00:00+00:00
 
5
Other values (16)
24 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters4400
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)6.8%

Sample

1st row2020-12-04T00:00:00+00:00
2nd row2020-12-04T00:00:00+00:00
3rd row2020-12-04T00:00:00+00:00
4th row2020-12-04T00:00:00+00:00
5th row2020-12-04T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-04T12:00:00+00:0097
55.1%
2020-12-04T17:00:00+00:0023
 
13.1%
2020-12-04T11:00:00+00:0022
 
12.5%
2020-12-04T00:00:00+00:005
 
2.8%
2020-12-04T04:00:00+00:005
 
2.8%
2020-12-04T09:00:00+00:004
 
2.3%
2020-12-04T05:00:00+00:003
 
1.7%
2020-12-04T21:00:00+00:003
 
1.7%
2020-12-04T14:00:00+00:002
 
1.1%
2020-12-04T14:45:00+00:001
 
0.6%
Other values (11)11
 
6.2%

Length

2022-09-05T21:37:27.958217image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-04t12:00:00+00:0097
55.1%
2020-12-04t17:00:00+00:0023
 
13.1%
2020-12-04t11:00:00+00:0022
 
12.5%
2020-12-04t00:00:00+00:005
 
2.8%
2020-12-04t04:00:00+00:005
 
2.8%
2020-12-04t09:00:00+00:004
 
2.3%
2020-12-04t05:00:00+00:003
 
1.7%
2020-12-04t21:00:00+00:003
 
1.7%
2020-12-04t14:00:00+00:002
 
1.1%
2020-12-04t14:15:00+00:001
 
0.6%
Other values (11)11
 
6.2%

Most occurring characters

ValueCountFrequency (%)
01952
44.4%
2629
 
14.3%
:528
 
12.0%
1354
 
8.0%
-352
 
8.0%
4185
 
4.2%
T176
 
4.0%
+176
 
4.0%
723
 
0.5%
511
 
0.2%
Other values (3)14
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3168
72.0%
Other Punctuation528
 
12.0%
Dash Punctuation352
 
8.0%
Uppercase Letter176
 
4.0%
Math Symbol176
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01952
61.6%
2629
 
19.9%
1354
 
11.2%
4185
 
5.8%
723
 
0.7%
511
 
0.3%
37
 
0.2%
95
 
0.2%
62
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:528
100.0%
Dash Punctuation
ValueCountFrequency (%)
-352
100.0%
Uppercase Letter
ValueCountFrequency (%)
T176
100.0%
Math Symbol
ValueCountFrequency (%)
+176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4224
96.0%
Latin176
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01952
46.2%
2629
 
14.9%
:528
 
12.5%
1354
 
8.4%
-352
 
8.3%
4185
 
4.4%
+176
 
4.2%
723
 
0.5%
511
 
0.3%
37
 
0.2%
Other values (2)7
 
0.2%
Latin
ValueCountFrequency (%)
T176
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01952
44.4%
2629
 
14.3%
:528
 
12.0%
1354
 
8.0%
-352
 
8.0%
4185
 
4.2%
T176
 
4.0%
+176
 
4.0%
723
 
0.5%
511
 
0.2%
Other values (3)14
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct51
Distinct (%)30.0%
Missing6
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean33.55882353
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:28.058383image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q120
median29
Q345
95-th percentile60
Maximum300
Range299
Interquartile range (IQR)25

Descriptive statistics

Standard deviation27.51201048
Coefficient of variation (CV)0.8198145103
Kurtosis52.299516
Mean33.55882353
Median Absolute Deviation (MAD)14
Skewness5.761123959
Sum5705
Variance756.9107205
MonotonicityNot monotonic
2022-09-05T21:37:28.174654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2711
 
6.2%
309
 
5.1%
459
 
5.1%
509
 
5.1%
158
 
4.5%
608
 
4.5%
298
 
4.5%
288
 
4.5%
237
 
4.0%
246
 
3.4%
Other values (41)87
49.4%
ValueCountFrequency (%)
11
 
0.6%
31
 
0.6%
53
1.7%
72
 
1.1%
84
2.3%
91
 
0.6%
104
2.3%
113
1.7%
125
2.8%
133
1.7%
ValueCountFrequency (%)
3001
 
0.6%
1202
 
1.1%
661
 
0.6%
608
4.5%
591
 
0.6%
581
 
0.6%
561
 
0.6%
556
3.4%
531
 
0.6%
509
5.1%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct88
Distinct (%)100.0%
Missing88
Missing (%)50.0%
Memory size1.5 KiB
<p>Simon is tormented by the mermaid's increasing demands for a blood payment. Stan suspects that the Masire brothers are behind Jazmine's disappearance.</p>
 
1
<p>When Fenton heads overseas to find Mrs. Khan's nephew, Rupert, he quickly realizes that whatever Rupert and Laura were working on garnered attention in Bridgeport. Meanwhile, Frank discovers an old note of his mom's in Bridgeport that mentions the sunken fishing boat and Joe and his new friend Biff befriend a man on the beach who asks them to help him by delivering a message.</p>
 
1
<p>After a devastating tragedy, Frank and Joe Hardy, together with their father Fenton, move to the small town of Bridgepoint to spend the summer with their Aunt Trudy. Their simple summer plans quickly come to an end when they discover their dad has taken on a secret investigation and Joe's life is threatened. Realizing that their Dad may be onto something, the boys take it upon themselves to start an investigation of their own.</p>
 
1
<p>Josh Johnson recalls fainting during a COVID test, meeting a baby with a very deep voice and finding his sex ed teacher on Facebook.</p>
 
1
<p>Bingo and Rolly go on a mission to help Santa and Mrs. Claus replace the lights on their friend's Hanukkiah.</p>
 
1
Other values (83)
83 

Length

Max length491
Median length172
Mean length197.1363636
Min length59

Characters and Unicode

Total characters17348
Distinct characters78
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st row<p>Randi must get over a mental barrier to say the E-word to Kim Rune. The couple Bitten and Reidar have had a one night stand.</p>
2nd row<p>Amelia Garayoa agrees to marry Santiago, a wealthy businessman who promises her a comfortable life.</p>
3rd row<p>Amelia settles in Buenos Aires; she finds Pierre having a cryptic conversation with Krisov.</p>
4th row<p>At sleep-away camp, Jessi befriends her trans cabinmate, and Nick discovers his two best friends have a little too much in common.</p><p><br /> </p>
5th row<p>After seeing their eighth grade classmates coupled up, Nick and Andrew make a play for two seventh grade girls. Jessi adjusts to life in the city.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p>Simon is tormented by the mermaid's increasing demands for a blood payment. Stan suspects that the Masire brothers are behind Jazmine's disappearance.</p>1
 
0.6%
<p>When Fenton heads overseas to find Mrs. Khan's nephew, Rupert, he quickly realizes that whatever Rupert and Laura were working on garnered attention in Bridgeport. Meanwhile, Frank discovers an old note of his mom's in Bridgeport that mentions the sunken fishing boat and Joe and his new friend Biff befriend a man on the beach who asks them to help him by delivering a message.</p>1
 
0.6%
<p>After a devastating tragedy, Frank and Joe Hardy, together with their father Fenton, move to the small town of Bridgepoint to spend the summer with their Aunt Trudy. Their simple summer plans quickly come to an end when they discover their dad has taken on a secret investigation and Joe's life is threatened. Realizing that their Dad may be onto something, the boys take it upon themselves to start an investigation of their own.</p>1
 
0.6%
<p>Josh Johnson recalls fainting during a COVID test, meeting a baby with a very deep voice and finding his sex ed teacher on Facebook.</p>1
 
0.6%
<p>Bingo and Rolly go on a mission to help Santa and Mrs. Claus replace the lights on their friend's Hanukkiah.</p>1
 
0.6%
<p>Auggie and Mo help recite their naptime Christmas story when the pages of their book go missing.</p>1
 
0.6%
<p>Mira must crack the case when Auntie Pushpa's gold purse and other valuables go missing.</p>1
 
0.6%
<p>When a mysterious girl arrives in Jalpur, Mira sets out on the case to figure out her true identity.</p>1
 
0.6%
<p>Director Justin Baldoni stumbles upon Zach Sobiech's story and sets out to find him. From their very first meeting, Justin realizes this young musician's story is special and that Zach's desire to make an impact before he leaves this world can inspire people everywhere.</p>1
 
0.6%
<p>When Tor's handsome face became the cause of Lin Lin's disaster, showing her masturbation in front of the whole world!</p><p>Introducing the first chapter of the series of short films; those would reveal the dark side of social media, the ugliest truths, those might be closer to you than you've ever imagined.</p>1
 
0.6%
Other values (78)78
44.3%
(Missing)88
50.0%

Length

2022-09-05T21:37:28.302553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the163
 
5.6%
to117
 
4.0%
and86
 
3.0%
a85
 
2.9%
of47
 
1.6%
with38
 
1.3%
his34
 
1.2%
in34
 
1.2%
their31
 
1.1%
p28
 
1.0%
Other values (1228)2234
77.1%

Most occurring characters

ValueCountFrequency (%)
2778
16.0%
e1586
 
9.1%
t1132
 
6.5%
a1046
 
6.0%
n971
 
5.6%
i960
 
5.5%
o929
 
5.4%
s866
 
5.0%
r828
 
4.8%
h705
 
4.1%
Other values (68)5547
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter12916
74.5%
Space Separator2813
 
16.2%
Uppercase Letter568
 
3.3%
Other Punctuation509
 
2.9%
Math Symbol500
 
2.9%
Dash Punctuation25
 
0.1%
Decimal Number14
 
0.1%
Open Punctuation1
 
< 0.1%
Initial Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1586
12.3%
t1132
 
8.8%
a1046
 
8.1%
n971
 
7.5%
i960
 
7.4%
o929
 
7.2%
s866
 
6.7%
r828
 
6.4%
h705
 
5.5%
l476
 
3.7%
Other values (16)3417
26.5%
Uppercase Letter
ValueCountFrequency (%)
M59
 
10.4%
S52
 
9.2%
B49
 
8.6%
T44
 
7.7%
A44
 
7.7%
J41
 
7.2%
F40
 
7.0%
C29
 
5.1%
K28
 
4.9%
E26
 
4.6%
Other values (15)156
27.5%
Other Punctuation
ValueCountFrequency (%)
.161
31.6%
/138
27.1%
,124
24.4%
'58
 
11.4%
?6
 
1.2%
!5
 
1.0%
;5
 
1.0%
5
 
1.0%
"4
 
0.8%
:3
 
0.6%
Decimal Number
ValueCountFrequency (%)
14
28.6%
04
28.6%
92
14.3%
81
 
7.1%
71
 
7.1%
31
 
7.1%
41
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
-19
76.0%
4
 
16.0%
2
 
8.0%
Space Separator
ValueCountFrequency (%)
2778
98.8%
 35
 
1.2%
Math Symbol
ValueCountFrequency (%)
>250
50.0%
<250
50.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13484
77.7%
Common3864
 
22.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1586
 
11.8%
t1132
 
8.4%
a1046
 
7.8%
n971
 
7.2%
i960
 
7.1%
o929
 
6.9%
s866
 
6.4%
r828
 
6.1%
h705
 
5.2%
l476
 
3.5%
Other values (41)3985
29.6%
Common
ValueCountFrequency (%)
2778
71.9%
>250
 
6.5%
<250
 
6.5%
.161
 
4.2%
/138
 
3.6%
,124
 
3.2%
'58
 
1.5%
 35
 
0.9%
-19
 
0.5%
?6
 
0.2%
Other values (17)45
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII17301
99.7%
None35
 
0.2%
Punctuation12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2778
16.1%
e1586
 
9.2%
t1132
 
6.5%
a1046
 
6.0%
n971
 
5.6%
i960
 
5.5%
o929
 
5.4%
s866
 
5.0%
r828
 
4.8%
h705
 
4.1%
Other values (63)5500
31.8%
None
ValueCountFrequency (%)
 35
100.0%
Punctuation
ValueCountFrequency (%)
5
41.7%
4
33.3%
2
 
16.7%
1
 
8.3%

rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct15
Distinct (%)50.0%
Missing146
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean7.986666667
Minimum6
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:28.395623image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile7.09
Q17.3
median7.85
Q38.775
95-th percentile9
Maximum9
Range3
Interquartile range (IQR)1.475

Descriptive statistics

Standard deviation0.8067531064
Coefficient of variation (CV)0.1010124925
Kurtosis-0.7598515412
Mean7.986666667
Median Absolute Deviation (MAD)0.65
Skewness-0.3047373429
Sum239.6
Variance0.6508505747
MonotonicityNot monotonic
2022-09-05T21:37:28.481175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
7.35
 
2.8%
94
 
2.3%
8.84
 
2.3%
8.73
 
1.7%
7.22
 
1.1%
7.42
 
1.1%
7.52
 
1.1%
8.51
 
0.6%
8.61
 
0.6%
8.21
 
0.6%
Other values (5)5
 
2.8%
(Missing)146
83.0%
ValueCountFrequency (%)
61
 
0.6%
71
 
0.6%
7.22
 
1.1%
7.35
2.8%
7.42
 
1.1%
7.52
 
1.1%
7.61
 
0.6%
7.71
 
0.6%
81
 
0.6%
8.21
 
0.6%
ValueCountFrequency (%)
94
2.3%
8.84
2.3%
8.73
1.7%
8.61
 
0.6%
8.51
 
0.6%
8.21
 
0.6%
81
 
0.6%
7.71
 
0.6%
7.61
 
0.6%
7.52
1.1%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
https://api.tvmaze.com/episodes/1984016
 
1
https://api.tvmaze.com/episodes/1961003
 
1
https://api.tvmaze.com/episodes/1969724
 
1
https://api.tvmaze.com/episodes/1976336
 
1
https://api.tvmaze.com/episodes/1976661
 
1
Other values (171)
171 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6864
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1984016
2nd rowhttps://api.tvmaze.com/episodes/1961003
3rd rowhttps://api.tvmaze.com/episodes/1976570
4th rowhttps://api.tvmaze.com/episodes/1976571
5th rowhttps://api.tvmaze.com/episodes/1979225

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19840161
 
0.6%
https://api.tvmaze.com/episodes/19610031
 
0.6%
https://api.tvmaze.com/episodes/19697241
 
0.6%
https://api.tvmaze.com/episodes/19763361
 
0.6%
https://api.tvmaze.com/episodes/19766611
 
0.6%
https://api.tvmaze.com/episodes/19740811
 
0.6%
https://api.tvmaze.com/episodes/19748181
 
0.6%
https://api.tvmaze.com/episodes/22460781
 
0.6%
https://api.tvmaze.com/episodes/19766441
 
0.6%
https://api.tvmaze.com/episodes/19792351
 
0.6%
Other values (166)166
94.3%

Length

2022-09-05T21:37:28.565170image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19840161
 
0.6%
https://api.tvmaze.com/episodes/19610031
 
0.6%
https://api.tvmaze.com/episodes/19832801
 
0.6%
https://api.tvmaze.com/episodes/19765701
 
0.6%
https://api.tvmaze.com/episodes/19765711
 
0.6%
https://api.tvmaze.com/episodes/19792251
 
0.6%
https://api.tvmaze.com/episodes/19725571
 
0.6%
https://api.tvmaze.com/episodes/19725581
 
0.6%
https://api.tvmaze.com/episodes/19104461
 
0.6%
https://api.tvmaze.com/episodes/20821721
 
0.6%
Other values (166)166
94.3%

Most occurring characters

ValueCountFrequency (%)
/704
 
10.3%
p528
 
7.7%
s528
 
7.7%
e528
 
7.7%
t528
 
7.7%
o352
 
5.1%
a352
 
5.1%
i352
 
5.1%
.352
 
5.1%
m352
 
5.1%
Other values (16)2288
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4400
64.1%
Other Punctuation1232
 
17.9%
Decimal Number1232
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p528
12.0%
s528
12.0%
e528
12.0%
t528
12.0%
o352
8.0%
a352
8.0%
i352
8.0%
m352
8.0%
h176
 
4.0%
d176
 
4.0%
Other values (3)528
12.0%
Decimal Number
ValueCountFrequency (%)
9238
19.3%
1208
16.9%
7147
11.9%
2123
10.0%
8104
8.4%
698
8.0%
095
 
7.7%
380
 
6.5%
570
 
5.7%
469
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/704
57.1%
.352
28.6%
:176
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4400
64.1%
Common2464
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/704
28.6%
.352
14.3%
9238
 
9.7%
1208
 
8.4%
:176
 
7.1%
7147
 
6.0%
2123
 
5.0%
8104
 
4.2%
698
 
4.0%
095
 
3.9%
Other values (3)219
 
8.9%
Latin
ValueCountFrequency (%)
p528
12.0%
s528
12.0%
e528
12.0%
t528
12.0%
o352
8.0%
a352
8.0%
i352
8.0%
m352
8.0%
h176
 
4.0%
d176
 
4.0%
Other values (3)528
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/704
 
10.3%
p528
 
7.7%
s528
 
7.7%
e528
 
7.7%
t528
 
7.7%
o352
 
5.1%
a352
 
5.1%
i352
 
5.1%
.352
 
5.1%
m352
 
5.1%
Other values (16)2288
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct91
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45627.9375
Minimum7564
Maximum62418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:28.665669image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum7564
5-th percentile22160.75
Q143601.75
median49940
Q352124
95-th percentile55299
Maximum62418
Range54854
Interquartile range (IQR)8522.25

Descriptive statistics

Standard deviation10702.28186
Coefficient of variation (CV)0.2345554597
Kurtosis2.541888658
Mean45627.9375
Median Absolute Deviation (MAD)2674
Skewness-1.671964199
Sum8030517
Variance114538836.9
MonotonicityNot monotonic
2022-09-05T21:37:28.784403image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4523513
 
7.4%
2875710
 
5.7%
400199
 
5.1%
497388
 
4.5%
499406
 
3.4%
519146
 
3.4%
521246
 
3.4%
523206
 
3.4%
504636
 
3.4%
524154
 
2.3%
Other values (81)102
58.0%
ValueCountFrequency (%)
75641
0.6%
80351
0.6%
115022
1.1%
131681
0.6%
152501
0.6%
173561
0.6%
191111
0.6%
210351
0.6%
225361
0.6%
249631
0.6%
ValueCountFrequency (%)
624181
 
0.6%
611401
 
0.6%
594954
2.3%
574911
 
0.6%
564331
 
0.6%
561391
 
0.6%
550191
 
0.6%
550161
 
0.6%
542181
 
0.6%
541121
 
0.6%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct91
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
https://www.tvmaze.com/shows/45235/the-hardy-boys
 
13
https://www.tvmaze.com/shows/28757/big-mouth
 
10
https://www.tvmaze.com/shows/40019/selena-the-series
 
9
https://www.tvmaze.com/shows/49738/binge-reloaded
 
8
https://www.tvmaze.com/shows/49940/earth-at-night-in-color
 
6
Other values (86)
130 

Length

Max length70
Median length63
Mean length50.6875
Min length39

Characters and Unicode

Total characters8921
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)37.5%

Sample

1st rowhttps://www.tvmaze.com/shows/48288/roast-battle-labelcom
2nd rowhttps://www.tvmaze.com/shows/48402/cuma
3rd rowhttps://www.tvmaze.com/shows/52118/zakon-i-besporyadok
4th rowhttps://www.tvmaze.com/shows/52118/zakon-i-besporyadok
5th rowhttps://www.tvmaze.com/shows/52198/kotiki

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/45235/the-hardy-boys13
 
7.4%
https://www.tvmaze.com/shows/28757/big-mouth10
 
5.7%
https://www.tvmaze.com/shows/40019/selena-the-series9
 
5.1%
https://www.tvmaze.com/shows/49738/binge-reloaded8
 
4.5%
https://www.tvmaze.com/shows/49940/earth-at-night-in-color6
 
3.4%
https://www.tvmaze.com/shows/51914/kings-of-joburg6
 
3.4%
https://www.tvmaze.com/shows/52124/bhaag-beanie-bhaag6
 
3.4%
https://www.tvmaze.com/shows/52320/el-estado-contra-pablo-ibar6
 
3.4%
https://www.tvmaze.com/shows/50463/stillwater6
 
3.4%
https://www.tvmaze.com/shows/52415/daughters4
 
2.3%
Other values (81)102
58.0%

Length

2022-09-05T21:37:28.900637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/45235/the-hardy-boys13
 
7.4%
https://www.tvmaze.com/shows/28757/big-mouth10
 
5.7%
https://www.tvmaze.com/shows/40019/selena-the-series9
 
5.1%
https://www.tvmaze.com/shows/49738/binge-reloaded8
 
4.5%
https://www.tvmaze.com/shows/49940/earth-at-night-in-color6
 
3.4%
https://www.tvmaze.com/shows/51914/kings-of-joburg6
 
3.4%
https://www.tvmaze.com/shows/52124/bhaag-beanie-bhaag6
 
3.4%
https://www.tvmaze.com/shows/52320/el-estado-contra-pablo-ibar6
 
3.4%
https://www.tvmaze.com/shows/50463/stillwater6
 
3.4%
https://www.tvmaze.com/shows/59495/bli-med-heim4
 
2.3%
Other values (81)102
58.0%

Most occurring characters

ValueCountFrequency (%)
/880
 
9.9%
w734
 
8.2%
t705
 
7.9%
s678
 
7.6%
o539
 
6.0%
e478
 
5.4%
h467
 
5.2%
m427
 
4.8%
a388
 
4.3%
.352
 
3.9%
Other values (30)3273
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6314
70.8%
Other Punctuation1408
 
15.8%
Decimal Number881
 
9.9%
Dash Punctuation318
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w734
11.6%
t705
11.2%
s678
10.7%
o539
 
8.5%
e478
 
7.6%
h467
 
7.4%
m427
 
6.8%
a388
 
6.1%
c226
 
3.6%
p209
 
3.3%
Other values (16)1463
23.2%
Decimal Number
ValueCountFrequency (%)
5163
18.5%
4129
14.6%
1111
12.6%
298
11.1%
084
9.5%
979
9.0%
369
7.8%
652
 
5.9%
750
 
5.7%
846
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/880
62.5%
.352
 
25.0%
:176
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6314
70.8%
Common2607
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w734
11.6%
t705
11.2%
s678
10.7%
o539
 
8.5%
e478
 
7.6%
h467
 
7.4%
m427
 
6.8%
a388
 
6.1%
c226
 
3.6%
p209
 
3.3%
Other values (16)1463
23.2%
Common
ValueCountFrequency (%)
/880
33.8%
.352
 
13.5%
-318
 
12.2%
:176
 
6.8%
5163
 
6.3%
4129
 
4.9%
1111
 
4.3%
298
 
3.8%
084
 
3.2%
979
 
3.0%
Other values (4)217
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII8921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/880
 
9.9%
w734
 
8.2%
t705
 
7.9%
s678
 
7.6%
o539
 
6.0%
e478
 
5.4%
h467
 
5.2%
m427
 
4.8%
a388
 
4.3%
.352
 
3.9%
Other values (30)3273
36.7%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct91
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
The Hardy Boys
 
13
Big Mouth
 
10
Selena: The Series
 
9
Binge Reloaded
 
8
Earth at Night in Color
 
6
Other values (86)
130 

Length

Max length35
Median length27
Mean length15.94886364
Min length4

Characters and Unicode

Total characters2807
Distinct characters92
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)37.5%

Sample

1st rowRoast Battle Labelcom
2nd rowЧума!
3rd rowZakon i Besporyadok
4th rowZakon i Besporyadok
5th rowКотики

Common Values

ValueCountFrequency (%)
The Hardy Boys13
 
7.4%
Big Mouth10
 
5.7%
Selena: The Series9
 
5.1%
Binge Reloaded8
 
4.5%
Earth at Night in Color6
 
3.4%
Kings of Jo'Burg6
 
3.4%
Bhaag Beanie Bhaag6
 
3.4%
El estado contra Pablo Ibar6
 
3.4%
Stillwater6
 
3.4%
Daughters4
 
2.3%
Other values (81)102
58.0%

Length

2022-09-05T21:37:29.015355image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the38
 
7.7%
boys14
 
2.9%
hardy13
 
2.6%
bhaag12
 
2.4%
mouth10
 
2.0%
big10
 
2.0%
selena9
 
1.8%
series9
 
1.8%
of9
 
1.8%
binge8
 
1.6%
Other values (210)359
73.1%

Most occurring characters

ValueCountFrequency (%)
315
 
11.2%
e277
 
9.9%
a195
 
6.9%
o170
 
6.1%
i153
 
5.5%
r143
 
5.1%
t128
 
4.6%
n127
 
4.5%
l107
 
3.8%
s106
 
3.8%
Other values (82)1086
38.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1998
71.2%
Uppercase Letter445
 
15.9%
Space Separator315
 
11.2%
Other Punctuation43
 
1.5%
Dash Punctuation3
 
0.1%
Decimal Number3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e277
13.9%
a195
 
9.8%
o170
 
8.5%
i153
 
7.7%
r143
 
7.2%
t128
 
6.4%
n127
 
6.4%
l107
 
5.4%
s106
 
5.3%
h96
 
4.8%
Other values (34)496
24.8%
Uppercase Letter
ValueCountFrequency (%)
B74
16.6%
T45
 
10.1%
S40
 
9.0%
M34
 
7.6%
C22
 
4.9%
E20
 
4.5%
P19
 
4.3%
H18
 
4.0%
W17
 
3.8%
D17
 
3.8%
Other values (28)139
31.2%
Other Punctuation
ValueCountFrequency (%)
:15
34.9%
.14
32.6%
'10
23.3%
,3
 
7.0%
!1
 
2.3%
Decimal Number
ValueCountFrequency (%)
01
33.3%
21
33.3%
51
33.3%
Space Separator
ValueCountFrequency (%)
315
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2388
85.1%
Common364
 
13.0%
Cyrillic55
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e277
 
11.6%
a195
 
8.2%
o170
 
7.1%
i153
 
6.4%
r143
 
6.0%
t128
 
5.4%
n127
 
5.3%
l107
 
4.5%
s106
 
4.4%
h96
 
4.0%
Other values (44)886
37.1%
Cyrillic
ValueCountFrequency (%)
а5
 
9.1%
и5
 
9.1%
у3
 
5.5%
к3
 
5.5%
с3
 
5.5%
р3
 
5.5%
о3
 
5.5%
т3
 
5.5%
К2
 
3.6%
д2
 
3.6%
Other values (18)23
41.8%
Common
ValueCountFrequency (%)
315
86.5%
:15
 
4.1%
.14
 
3.8%
'10
 
2.7%
,3
 
0.8%
-3
 
0.8%
01
 
0.3%
21
 
0.3%
!1
 
0.3%
51
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2744
97.8%
Cyrillic55
 
2.0%
None8
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
315
 
11.5%
e277
 
10.1%
a195
 
7.1%
o170
 
6.2%
i153
 
5.6%
r143
 
5.2%
t128
 
4.7%
n127
 
4.6%
l107
 
3.9%
s106
 
3.9%
Other values (50)1023
37.3%
Cyrillic
ValueCountFrequency (%)
а5
 
9.1%
и5
 
9.1%
у3
 
5.5%
к3
 
5.5%
с3
 
5.5%
р3
 
5.5%
о3
 
5.5%
т3
 
5.5%
К2
 
3.6%
д2
 
3.6%
Other values (18)23
41.8%
None
ValueCountFrequency (%)
ø4
50.0%
é2
25.0%
ä1
 
12.5%
ş1
 
12.5%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Scripted
83 
Animation
35 
Documentary
29 
Talk Show
 
8
Reality
 
7
Other values (5)
14 

Length

Max length11
Median length10
Mean length8.676136364
Min length4

Characters and Unicode

Total characters1527
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st rowGame Show
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted83
47.2%
Animation35
19.9%
Documentary29
 
16.5%
Talk Show8
 
4.5%
Reality7
 
4.0%
Game Show6
 
3.4%
Variety4
 
2.3%
Sports2
 
1.1%
Award Show1
 
0.6%
News1
 
0.6%

Length

2022-09-05T21:37:29.119542image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:29.231443image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted83
43.5%
animation35
18.3%
documentary29
 
15.2%
show15
 
7.9%
talk8
 
4.2%
reality7
 
3.7%
game6
 
3.1%
variety4
 
2.1%
sports2
 
1.0%
award1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
i164
10.7%
t160
10.5%
e130
 
8.5%
r119
 
7.8%
c112
 
7.3%
S100
 
6.5%
n99
 
6.5%
a90
 
5.9%
p85
 
5.6%
d84
 
5.5%
Other values (17)384
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1321
86.5%
Uppercase Letter191
 
12.5%
Space Separator15
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i164
12.4%
t160
12.1%
e130
9.8%
r119
9.0%
c112
8.5%
n99
7.5%
a90
6.8%
p85
6.4%
d84
6.4%
o81
6.1%
Other values (8)197
14.9%
Uppercase Letter
ValueCountFrequency (%)
S100
52.4%
A36
 
18.8%
D29
 
15.2%
T8
 
4.2%
R7
 
3.7%
G6
 
3.1%
V4
 
2.1%
N1
 
0.5%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1512
99.0%
Common15
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i164
10.8%
t160
10.6%
e130
 
8.6%
r119
 
7.9%
c112
 
7.4%
S100
 
6.6%
n99
 
6.5%
a90
 
6.0%
p85
 
5.6%
d84
 
5.6%
Other values (16)369
24.4%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i164
10.7%
t160
10.5%
e130
 
8.5%
r119
 
7.8%
c112
 
7.3%
S100
 
6.5%
n99
 
6.5%
a90
 
5.9%
p85
 
5.6%
d84
 
5.5%
Other values (17)384
25.1%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
English
87 
Norwegian
15 
Chinese
11 
Russian
German
Other values (11)
45 

Length

Max length10
Median length7
Mean length6.909090909
Min length4

Characters and Unicode

Total characters1216
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English87
49.4%
Norwegian15
 
8.5%
Chinese11
 
6.2%
Russian9
 
5.1%
German9
 
5.1%
Spanish9
 
5.1%
Korean8
 
4.5%
Hindi7
 
4.0%
Thai5
 
2.8%
Tagalog4
 
2.3%
Other values (6)12
 
6.8%

Length

2022-09-05T21:37:29.329421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english87
49.4%
norwegian15
 
8.5%
chinese11
 
6.2%
russian9
 
5.1%
german9
 
5.1%
spanish9
 
5.1%
korean8
 
4.5%
hindi7
 
4.0%
thai5
 
2.8%
tagalog4
 
2.3%
Other values (6)12
 
6.8%

Most occurring characters

ValueCountFrequency (%)
n160
13.2%
i155
12.7%
s130
10.7%
h118
9.7%
g112
9.2%
l94
7.7%
E87
7.2%
a71
 
5.8%
e61
 
5.0%
r37
 
3.0%
Other values (22)191
15.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1040
85.5%
Uppercase Letter176
 
14.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n160
15.4%
i155
14.9%
s130
12.5%
h118
11.3%
g112
10.8%
l94
9.0%
a71
6.8%
e61
 
5.9%
r37
 
3.6%
o29
 
2.8%
Other values (8)73
7.0%
Uppercase Letter
ValueCountFrequency (%)
E87
49.4%
N15
 
8.5%
C11
 
6.2%
T11
 
6.2%
S9
 
5.1%
G9
 
5.1%
R9
 
5.1%
K8
 
4.5%
H7
 
4.0%
D3
 
1.7%
Other values (4)7
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1216
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n160
13.2%
i155
12.7%
s130
10.7%
h118
9.7%
g112
9.2%
l94
7.7%
E87
7.2%
a71
 
5.8%
e61
 
5.0%
r37
 
3.0%
Other values (22)191
15.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n160
13.2%
i155
12.7%
s130
10.7%
h118
9.7%
g112
9.2%
l94
7.7%
E87
7.2%
a71
 
5.8%
e61
 
5.0%
r37
 
3.0%
Other values (22)191
15.7%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.5 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Running
76 
To Be Determined
53 
Ended
47 

Length

Max length16
Median length7
Mean length9.176136364
Min length5

Characters and Unicode

Total characters1615
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Running76
43.2%
To Be Determined53
30.1%
Ended47
26.7%

Length

2022-09-05T21:37:29.416450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:29.506523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running76
27.0%
to53
18.8%
be53
18.8%
determined53
18.8%
ended47
16.7%

Most occurring characters

ValueCountFrequency (%)
n328
20.3%
e259
16.0%
d147
9.1%
i129
 
8.0%
106
 
6.6%
R76
 
4.7%
u76
 
4.7%
g76
 
4.7%
T53
 
3.3%
o53
 
3.3%
Other values (6)312
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1227
76.0%
Uppercase Letter282
 
17.5%
Space Separator106
 
6.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n328
26.7%
e259
21.1%
d147
12.0%
i129
 
10.5%
u76
 
6.2%
g76
 
6.2%
o53
 
4.3%
t53
 
4.3%
r53
 
4.3%
m53
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
R76
27.0%
T53
18.8%
B53
18.8%
D53
18.8%
E47
16.7%
Space Separator
ValueCountFrequency (%)
106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1509
93.4%
Common106
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n328
21.7%
e259
17.2%
d147
9.7%
i129
 
8.5%
R76
 
5.0%
u76
 
5.0%
g76
 
5.0%
T53
 
3.5%
o53
 
3.5%
B53
 
3.5%
Other values (5)259
17.2%
Common
ValueCountFrequency (%)
106
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n328
20.3%
e259
16.0%
d147
9.1%
i129
 
8.0%
106
 
6.6%
R76
 
4.7%
u76
 
4.7%
g76
 
4.7%
T53
 
3.3%
o53
 
3.3%
Other values (6)312
19.3%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)30.0%
Missing96
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean37.725
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:29.585759image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q115
median30
Q350
95-th percentile63
Maximum300
Range299
Interquartile range (IQR)35

Descriptive statistics

Standard deviation38.9670341
Coefficient of variation (CV)1.032923369
Kurtosis25.84586685
Mean37.725
Median Absolute Deviation (MAD)19
Skewness4.218207434
Sum3018
Variance1518.429747
MonotonicityNot monotonic
2022-09-05T21:37:29.680551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
508
 
4.5%
158
 
4.5%
308
 
4.5%
608
 
4.5%
457
 
4.0%
556
 
3.4%
105
 
2.8%
204
 
2.3%
1203
 
1.7%
53
 
1.7%
Other values (14)20
 
11.4%
(Missing)96
54.5%
ValueCountFrequency (%)
11
 
0.6%
31
 
0.6%
53
 
1.7%
71
 
0.6%
82
 
1.1%
105
2.8%
112
 
1.1%
123
 
1.7%
141
 
0.6%
158
4.5%
ValueCountFrequency (%)
3001
 
0.6%
1203
 
1.7%
608
4.5%
556
3.4%
508
4.5%
481
 
0.6%
457
4.0%
401
 
0.6%
308
4.5%
281
 
0.6%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct39
Distinct (%)22.5%
Missing3
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean33.99421965
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:31.185255image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.6
Q118
median29
Q345
95-th percentile60
Maximum300
Range299
Interquartile range (IQR)27

Descriptive statistics

Standard deviation27.83036177
Coefficient of variation (CV)0.8186792358
Kurtosis48.67358312
Mean33.99421965
Median Absolute Deviation (MAD)14
Skewness5.48778603
Sum5881
Variance774.5290362
MonotonicityNot monotonic
2022-09-05T21:37:31.287921image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2915
 
8.5%
4313
 
7.4%
2710
 
5.7%
379
 
5.1%
609
 
5.1%
538
 
4.5%
158
 
4.5%
287
 
4.0%
507
 
4.0%
556
 
3.4%
Other values (29)81
46.0%
ValueCountFrequency (%)
11
 
0.6%
31
 
0.6%
54
2.3%
83
1.7%
91
 
0.6%
103
1.7%
116
3.4%
124
2.3%
135
2.8%
145
2.8%
ValueCountFrequency (%)
3001
 
0.6%
1202
 
1.1%
981
 
0.6%
609
5.1%
556
3.4%
542
 
1.1%
538
4.5%
507
4.0%
482
 
1.1%
461
 
0.6%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct66
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2020-12-04
76 
2017-09-29
10 
2020-11-27
 
5
2018-01-02
 
4
2020-11-06
 
4
Other values (61)
77 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1760
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)26.1%

Sample

1st row2019-12-24
2nd row2020-05-29
3rd row2020-11-27
4th row2020-11-27
5th row2020-11-30

Common Values

ValueCountFrequency (%)
2020-12-0476
43.2%
2017-09-2910
 
5.7%
2020-11-275
 
2.8%
2018-01-024
 
2.3%
2020-11-064
 
2.3%
2019-10-103
 
1.7%
2019-06-142
 
1.1%
2020-11-242
 
1.1%
2020-11-192
 
1.1%
2012-01-282
 
1.1%
Other values (56)66
37.5%

Length

2022-09-05T21:37:31.376882image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0476
43.2%
2017-09-2910
 
5.7%
2020-11-275
 
2.8%
2018-01-024
 
2.3%
2020-11-064
 
2.3%
2019-10-103
 
1.7%
2020-10-292
 
1.1%
2020-09-182
 
1.1%
2020-09-112
 
1.1%
2020-11-182
 
1.1%
Other values (56)66
37.5%

Most occurring characters

ValueCountFrequency (%)
0478
27.2%
2436
24.8%
-352
20.0%
1258
14.7%
495
 
5.4%
956
 
3.2%
727
 
1.5%
821
 
1.2%
613
 
0.7%
313
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1408
80.0%
Dash Punctuation352
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0478
33.9%
2436
31.0%
1258
18.3%
495
 
6.7%
956
 
4.0%
727
 
1.9%
821
 
1.5%
613
 
0.9%
313
 
0.9%
511
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
-352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0478
27.2%
2436
24.8%
-352
20.0%
1258
14.7%
495
 
5.4%
956
 
3.2%
727
 
1.5%
821
 
1.2%
613
 
0.7%
313
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0478
27.2%
2436
24.8%
-352
20.0%
1258
14.7%
495
 
5.4%
956
 
3.2%
727
 
1.5%
821
 
1.2%
613
 
0.7%
313
 
0.7%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct20
Distinct (%)42.6%
Missing129
Missing (%)73.3%
Memory size1.5 KiB
2021-05-04
2020-12-04
2020-12-11
2020-12-25
2021-01-04
Other values (15)
18 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters470
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)25.5%

Sample

1st row2020-12-18
2nd row2020-12-11
3rd row2020-12-11
4th row2020-12-11
5th row2021-01-04

Common Values

ValueCountFrequency (%)
2021-05-049
 
5.1%
2020-12-048
 
4.5%
2020-12-115
 
2.8%
2020-12-255
 
2.8%
2021-01-042
 
1.1%
2021-01-142
 
1.1%
2021-01-222
 
1.1%
2021-01-012
 
1.1%
2021-01-291
 
0.6%
2021-03-131
 
0.6%
Other values (10)10
 
5.7%
(Missing)129
73.3%

Length

2022-09-05T21:37:31.453619image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-05-049
19.1%
2020-12-048
17.0%
2020-12-115
10.6%
2020-12-255
10.6%
2021-01-042
 
4.3%
2021-01-142
 
4.3%
2021-01-222
 
4.3%
2021-01-012
 
4.3%
2021-10-021
 
2.1%
2021-02-121
 
2.1%
Other values (10)10
21.3%

Most occurring characters

ValueCountFrequency (%)
2133
28.3%
0120
25.5%
-94
20.0%
177
16.4%
422
 
4.7%
516
 
3.4%
33
 
0.6%
83
 
0.6%
91
 
0.2%
61
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number376
80.0%
Dash Punctuation94
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2133
35.4%
0120
31.9%
177
20.5%
422
 
5.9%
516
 
4.3%
33
 
0.8%
83
 
0.8%
91
 
0.3%
61
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2133
28.3%
0120
25.5%
-94
20.0%
177
16.4%
422
 
4.7%
516
 
3.4%
33
 
0.6%
83
 
0.6%
91
 
0.2%
61
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2133
28.3%
0120
25.5%
-94
20.0%
177
16.4%
422
 
4.7%
516
 
3.4%
33
 
0.6%
83
 
0.6%
91
 
0.2%
61
 
0.2%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct83
Distinct (%)52.2%
Missing17
Missing (%)9.7%
Memory size1.5 KiB
https://www.hulu.com/series/the-hardy-boys-5b8279f9-40eb-49e3-a42e-d80ce343e658
13 
https://www.netflix.com/title/80117038
 
10
https://www.netflix.com/title/81022733
 
9
https://www.amazon.de/dp/B08N8ZMF8Y/
 
8
https://tv.apple.com/us/show/earth-at-night-in-color/umc.cmc.37dvcdop7ub4m8tx9fnczl1a1
 
6
Other values (78)
113 

Length

Max length166
Median length74
Mean length52.09433962
Min length16

Characters and Unicode

Total characters8283
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)39.0%

Sample

1st rowhttps://www.youtube.com/playlist?list=PLmkbS48df311cZnmhlV-5q5vY0icLXdl3
2nd rowhttps://www.ivi.ru/watch/chuma-2020
3rd rowhttps://www.ivi.ru/watch/zakon-i-besporyadok
4th rowhttps://www.ivi.ru/watch/zakon-i-besporyadok
5th rowhttp://epic-media.ru/project/kotiki

Common Values

ValueCountFrequency (%)
https://www.hulu.com/series/the-hardy-boys-5b8279f9-40eb-49e3-a42e-d80ce343e65813
 
7.4%
https://www.netflix.com/title/8011703810
 
5.7%
https://www.netflix.com/title/810227339
 
5.1%
https://www.amazon.de/dp/B08N8ZMF8Y/8
 
4.5%
https://tv.apple.com/us/show/earth-at-night-in-color/umc.cmc.37dvcdop7ub4m8tx9fnczl1a16
 
3.4%
https://www.netflix.com/title/812198046
 
3.4%
https://tv.apple.com/us/show/stillwater/umc.cmc.3czcagetjq31vvbgkkyp1xiao6
 
3.4%
https://www.netflix.com/title/810180576
 
3.4%
https://tv.nrk.no/serie/bli-med-heim4
 
2.3%
https://www.iq.com/play/1n40eysnffc4
 
2.3%
Other values (73)87
49.4%
(Missing)17
 
9.7%

Length

2022-09-05T21:37:31.560761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.hulu.com/series/the-hardy-boys-5b8279f9-40eb-49e3-a42e-d80ce343e65813
 
8.2%
https://www.netflix.com/title/8011703810
 
6.3%
https://www.netflix.com/title/810227339
 
5.7%
https://www.amazon.de/dp/b08n8zmf8y8
 
5.0%
https://tv.apple.com/us/show/earth-at-night-in-color/umc.cmc.37dvcdop7ub4m8tx9fnczl1a16
 
3.8%
https://www.netflix.com/title/812198046
 
3.8%
https://tv.apple.com/us/show/stillwater/umc.cmc.3czcagetjq31vvbgkkyp1xiao6
 
3.8%
https://www.netflix.com/title/810180576
 
3.8%
https://tv.nrk.no/serie/bli-med-heim4
 
2.5%
https://www.iq.com/play/1n40eysnffc4
 
2.5%
Other values (73)87
54.7%

Most occurring characters

ValueCountFrequency (%)
/698
 
8.4%
t654
 
7.9%
e468
 
5.7%
s411
 
5.0%
w398
 
4.8%
o359
 
4.3%
.328
 
4.0%
h303
 
3.7%
i299
 
3.6%
c282
 
3.4%
Other values (61)4083
49.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5577
67.3%
Other Punctuation1201
 
14.5%
Decimal Number950
 
11.5%
Uppercase Letter280
 
3.4%
Dash Punctuation244
 
2.9%
Math Symbol18
 
0.2%
Connector Punctuation13
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t654
 
11.7%
e468
 
8.4%
s411
 
7.4%
w398
 
7.1%
o359
 
6.4%
h303
 
5.4%
i299
 
5.4%
c282
 
5.1%
p272
 
4.9%
m260
 
4.7%
Other values (16)1871
33.5%
Uppercase Letter
ValueCountFrequency (%)
N18
 
6.4%
Z18
 
6.4%
B17
 
6.1%
Y17
 
6.1%
P16
 
5.7%
F15
 
5.4%
A14
 
5.0%
D14
 
5.0%
L14
 
5.0%
U13
 
4.6%
Other values (16)124
44.3%
Decimal Number
ValueCountFrequency (%)
8144
15.2%
0132
13.9%
1122
12.8%
3110
11.6%
4101
10.6%
981
8.5%
281
8.5%
780
8.4%
558
6.1%
641
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/698
58.1%
.328
27.3%
:159
 
13.2%
?12
 
1.0%
&4
 
0.3%
Math Symbol
ValueCountFrequency (%)
=16
88.9%
~2
 
11.1%
Dash Punctuation
ValueCountFrequency (%)
-244
100.0%
Connector Punctuation
ValueCountFrequency (%)
_13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5857
70.7%
Common2426
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t654
 
11.2%
e468
 
8.0%
s411
 
7.0%
w398
 
6.8%
o359
 
6.1%
h303
 
5.2%
i299
 
5.1%
c282
 
4.8%
p272
 
4.6%
m260
 
4.4%
Other values (42)2151
36.7%
Common
ValueCountFrequency (%)
/698
28.8%
.328
13.5%
-244
 
10.1%
:159
 
6.6%
8144
 
5.9%
0132
 
5.4%
1122
 
5.0%
3110
 
4.5%
4101
 
4.2%
981
 
3.3%
Other values (9)307
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII8283
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/698
 
8.4%
t654
 
7.9%
e468
 
5.7%
s411
 
5.0%
w398
 
4.8%
o359
 
4.3%
.328
 
4.0%
h303
 
3.7%
i299
 
3.6%
c282
 
3.4%
Other values (61)4083
49.3%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
146 
20:00
 
6
12:00
 
5
06:00
 
3
21:00
 
3
Other values (8)
 
13

Length

Max length5
Median length0
Mean length0.8522727273
Min length0

Characters and Unicode

Total characters150
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)1.7%

Sample

1st row
2nd row
3rd row12:00
4th row12:00
5th row10:00

Common Values

ValueCountFrequency (%)
146
83.0%
20:006
 
3.4%
12:005
 
2.8%
06:003
 
1.7%
21:003
 
1.7%
10:002
 
1.1%
18:002
 
1.1%
00:002
 
1.1%
08:302
 
1.1%
08:002
 
1.1%
Other values (3)3
 
1.7%

Length

2022-09-05T21:37:31.657648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:006
20.0%
12:005
16.7%
06:003
10.0%
21:003
10.0%
10:002
 
6.7%
18:002
 
6.7%
00:002
 
6.7%
08:302
 
6.7%
08:002
 
6.7%
22:451
 
3.3%
Other values (2)2
 
6.7%

Most occurring characters

ValueCountFrequency (%)
074
49.3%
:30
20.0%
219
 
12.7%
112
 
8.0%
86
 
4.0%
63
 
2.0%
53
 
2.0%
32
 
1.3%
41
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number120
80.0%
Other Punctuation30
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
074
61.7%
219
 
15.8%
112
 
10.0%
86
 
5.0%
63
 
2.5%
53
 
2.5%
32
 
1.7%
41
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
074
49.3%
:30
20.0%
219
 
12.7%
112
 
8.0%
86
 
4.0%
63
 
2.0%
53
 
2.0%
32
 
1.3%
41
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
074
49.3%
:30
20.0%
219
 
12.7%
112
 
8.0%
86
 
4.0%
63
 
2.0%
53
 
2.0%
32
 
1.3%
41
 
0.7%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.5 KiB

_embedded.show.rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct11
Distinct (%)21.2%
Missing124
Missing (%)70.5%
Infinite0
Infinite (%)0.0%
Mean6.903846154
Minimum5
Maximum8.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:31.729903image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.3
Q16.6
median7
Q37.4
95-th percentile7.8
Maximum8.6
Range3.6
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.813359419
Coefficient of variation (CV)0.1178125064
Kurtosis0.280555393
Mean6.903846154
Median Absolute Deviation (MAD)0.4
Skewness-0.7532330953
Sum359
Variance0.6615535445
MonotonicityNot monotonic
2022-09-05T21:37:31.810883image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
713
 
7.4%
7.810
 
5.7%
6.69
 
5.1%
7.46
 
3.4%
5.36
 
3.4%
7.23
 
1.7%
61
 
0.6%
6.41
 
0.6%
8.61
 
0.6%
51
 
0.6%
(Missing)124
70.5%
ValueCountFrequency (%)
51
 
0.6%
5.36
3.4%
61
 
0.6%
6.41
 
0.6%
6.69
5.1%
6.81
 
0.6%
713
7.4%
7.23
 
1.7%
7.46
3.4%
7.810
5.7%
ValueCountFrequency (%)
8.61
 
0.6%
7.810
5.7%
7.46
3.4%
7.23
 
1.7%
713
7.4%
6.81
 
0.6%
6.69
5.1%
6.41
 
0.6%
61
 
0.6%
5.36
3.4%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct59
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.23863636
Minimum2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:31.913139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q127.75
median41
Q378.25
95-th percentile97
Maximum100
Range98
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation29.62199735
Coefficient of variation (CV)0.6016006848
Kurtosis-1.07119472
Mean49.23863636
Median Absolute Deviation (MAD)20
Skewness0.3192721409
Sum8666
Variance877.4627273
MonotonicityNot monotonic
2022-09-05T21:37:32.029762image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3516
 
9.1%
9513
 
7.4%
9710
 
5.7%
519
 
5.1%
158
 
4.5%
436
 
3.4%
386
 
3.4%
946
 
3.4%
906
 
3.4%
406
 
3.4%
Other values (49)90
51.1%
ValueCountFrequency (%)
24
2.3%
34
2.3%
42
 
1.1%
61
 
0.6%
71
 
0.6%
82
 
1.1%
92
 
1.1%
111
 
0.6%
142
 
1.1%
158
4.5%
ValueCountFrequency (%)
1001
 
0.6%
9710
5.7%
9513
7.4%
946
3.4%
906
3.4%
831
 
0.6%
821
 
0.6%
801
 
0.6%
795
 
2.8%
781
 
0.6%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)25.1%
Missing5
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean133.4561404
Minimum1
Maximum510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:32.133111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median73
Q3266
95-th percentile434
Maximum510
Range509
Interquartile range (IQR)264

Descriptive statistics

Standard deviation146.3742669
Coefficient of variation (CV)1.096796794
Kurtosis-0.7865434002
Mean133.4561404
Median Absolute Deviation (MAD)72
Skewness0.7709204747
Sum22821
Variance21425.42601
MonotonicityNot monotonic
2022-09-05T21:37:32.245189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
131
17.6%
2122
12.5%
213
 
7.4%
31012
 
6.8%
2388
 
4.5%
38
 
4.5%
2878
 
4.5%
837
 
4.0%
4346
 
3.4%
1045
 
2.8%
Other values (33)51
29.0%
ValueCountFrequency (%)
131
17.6%
213
7.4%
38
 
4.5%
121
 
0.6%
151
 
0.6%
2122
12.5%
302
 
1.1%
511
 
0.6%
541
 
0.6%
675
 
2.8%
ValueCountFrequency (%)
5101
 
0.6%
4641
 
0.6%
4401
 
0.6%
4391
 
0.6%
4346
3.4%
4161
 
0.6%
4101
 
0.6%
4051
 
0.6%
3521
 
0.6%
3471
 
0.6%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct43
Distinct (%)25.1%
Missing5
Missing (%)2.8%
Memory size1.5 KiB
Netflix
31 
YouTube
22 
Hulu
13 
Apple TV+
12 
NRK TV
 
8
Other values (38)
85 

Length

Max length15
Median length14
Mean length7.49122807
Min length3

Characters and Unicode

Total characters1281
Distinct characters53
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)13.5%

Sample

1st rowYouTube
2nd rowivi
3rd rowivi
4th rowivi
5th rowEpic Media

Common Values

ValueCountFrequency (%)
Netflix31
17.6%
YouTube22
12.5%
Hulu13
 
7.4%
Apple TV+12
 
6.8%
NRK TV8
 
4.5%
Prime Video8
 
4.5%
Disney+8
 
4.5%
DisneyNOW7
 
4.0%
HBO España6
 
3.4%
Tencent QQ5
 
2.8%
Other values (33)51
29.0%

Length

2022-09-05T21:37:32.341263image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
netflix31
 
13.7%
youtube22
 
9.7%
tv22
 
9.7%
hulu13
 
5.7%
apple12
 
5.3%
hbo9
 
4.0%
nrk8
 
3.5%
prime8
 
3.5%
video8
 
3.5%
disney8
 
3.5%
Other values (48)86
37.9%

Most occurring characters

ValueCountFrequency (%)
e126
 
9.8%
i95
 
7.4%
u79
 
6.2%
l67
 
5.2%
T57
 
4.4%
56
 
4.4%
o55
 
4.3%
N51
 
4.0%
t51
 
4.0%
V44
 
3.4%
Other values (43)600
46.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter823
64.2%
Uppercase Letter373
29.1%
Space Separator56
 
4.4%
Math Symbol28
 
2.2%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e126
15.3%
i95
11.5%
u79
 
9.6%
l67
 
8.1%
o55
 
6.7%
t51
 
6.2%
a37
 
4.5%
x36
 
4.4%
n34
 
4.1%
p32
 
3.9%
Other values (15)211
25.6%
Uppercase Letter
ValueCountFrequency (%)
T57
15.3%
N51
13.7%
V44
11.8%
Y29
 
7.8%
H24
 
6.4%
O19
 
5.1%
D16
 
4.3%
Q15
 
4.0%
I13
 
3.5%
W12
 
3.2%
Other values (14)93
24.9%
Math Symbol
ValueCountFrequency (%)
+27
96.4%
|1
 
3.6%
Space Separator
ValueCountFrequency (%)
56
100.0%
Other Punctuation
ValueCountFrequency (%)
:1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1196
93.4%
Common85
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e126
 
10.5%
i95
 
7.9%
u79
 
6.6%
l67
 
5.6%
T57
 
4.8%
o55
 
4.6%
N51
 
4.3%
t51
 
4.3%
V44
 
3.7%
a37
 
3.1%
Other values (39)534
44.6%
Common
ValueCountFrequency (%)
56
65.9%
+27
31.8%
:1
 
1.2%
|1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1275
99.5%
None6
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e126
 
9.9%
i95
 
7.5%
u79
 
6.2%
l67
 
5.3%
T57
 
4.5%
56
 
4.4%
o55
 
4.3%
N51
 
4.0%
t51
 
4.0%
V44
 
3.5%
Other values (42)594
46.6%
None
ValueCountFrequency (%)
ñ6
100.0%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct20
Distinct (%)15.9%
Missing50
Missing (%)28.4%
Memory size1.5 KiB
https://www.netflix.com/
31 
https://www.youtube.com
22 
https://www.hulu.com/
13 
https://tv.apple.com/
12 
https://www.primevideo.com
Other values (15)
40 

Length

Max length34
Median length27
Mean length23.02380952
Min length17

Characters and Unicode

Total characters2901
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.8%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://www.ivi.ru/
3rd rowhttps://www.ivi.ru/
4th rowhttps://www.ivi.ru/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.netflix.com/31
17.6%
https://www.youtube.com22
12.5%
https://www.hulu.com/13
 
7.4%
https://tv.apple.com/12
 
6.8%
https://www.primevideo.com8
 
4.5%
https://www.disneyplus.com/8
 
4.5%
https://www.iq.com/5
 
2.8%
https://v.qq.com/5
 
2.8%
https://www.discoveryplus.com/3
 
1.7%
https://www.ivi.ru/3
 
1.7%
Other values (10)16
 
9.1%
(Missing)50
28.4%

Length

2022-09-05T21:37:32.433604image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com31
24.6%
https://www.youtube.com22
17.5%
https://www.hulu.com13
10.3%
https://tv.apple.com12
 
9.5%
https://www.primevideo.com8
 
6.3%
https://www.disneyplus.com8
 
6.3%
https://www.iq.com5
 
4.0%
https://v.qq.com5
 
4.0%
https://www.hbomax.com3
 
2.4%
https://www.viki.com3
 
2.4%
Other values (10)16
12.7%

Most occurring characters

ValueCountFrequency (%)
/347
12.0%
t327
11.3%
w318
11.0%
.253
 
8.7%
p172
 
5.9%
o164
 
5.7%
s151
 
5.2%
h144
 
5.0%
m139
 
4.8%
c128
 
4.4%
Other values (17)758
26.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2175
75.0%
Other Punctuation726
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t327
15.0%
w318
14.6%
p172
 
7.9%
o164
 
7.5%
s151
 
6.9%
h144
 
6.6%
m139
 
6.4%
c128
 
5.9%
e100
 
4.6%
u86
 
4.0%
Other values (14)446
20.5%
Other Punctuation
ValueCountFrequency (%)
/347
47.8%
.253
34.8%
:126
 
17.4%

Most occurring scripts

ValueCountFrequency (%)
Latin2175
75.0%
Common726
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t327
15.0%
w318
14.6%
p172
 
7.9%
o164
 
7.5%
s151
 
6.9%
h144
 
6.6%
m139
 
6.4%
c128
 
5.9%
e100
 
4.6%
u86
 
4.0%
Other values (14)446
20.5%
Common
ValueCountFrequency (%)
/347
47.8%
.253
34.8%
:126
 
17.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2901
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/347
12.0%
t327
11.3%
w318
11.0%
.253
 
8.7%
p172
 
5.9%
o164
 
5.7%
s151
 
5.2%
h144
 
5.0%
m139
 
4.8%
c128
 
4.4%
Other values (17)758
26.1%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)66.7%
Missing173
Missing (%)98.3%
Memory size1.5 KiB
34149.0
47170.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters21
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row47170.0
2nd row34149.0
3rd row34149.0

Common Values

ValueCountFrequency (%)
34149.02
 
1.1%
47170.01
 
0.6%
(Missing)173
98.3%

Length

2022-09-05T21:37:32.518032image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:32.613404image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
34149.02
66.7%
47170.01
33.3%

Most occurring characters

ValueCountFrequency (%)
45
23.8%
04
19.0%
13
14.3%
.3
14.3%
32
 
9.5%
92
 
9.5%
72
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18
85.7%
Other Punctuation3
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
45
27.8%
04
22.2%
13
16.7%
32
 
11.1%
92
 
11.1%
72
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
45
23.8%
04
19.0%
13
14.3%
.3
14.3%
32
 
9.5%
92
 
9.5%
72
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
23.8%
04
19.0%
13
14.3%
.3
14.3%
32
 
9.5%
92
 
9.5%
72
 
9.5%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)49.6%
Missing49
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean367549.3543
Minimum252077
Maximum411923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:32.707705image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum252077
5-th percentile282280.2
Q1358934
median386560
Q3391628
95-th percentile392934
Maximum411923
Range159846
Interquartile range (IQR)32694

Descriptive statistics

Standard deviation35495.1756
Coefficient of variation (CV)0.09657254239
Kurtosis2.08373905
Mean367549.3543
Median Absolute Deviation (MAD)6374
Skewness-1.644470026
Sum46678768
Variance1259907491
MonotonicityNot monotonic
2022-09-05T21:37:32.826219image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39162813
 
7.4%
33143110
 
5.7%
3684539
 
5.1%
3929346
 
3.4%
3865606
 
3.4%
3928366
 
3.4%
3901286
 
3.4%
3895543
 
1.7%
3707853
 
1.7%
3915623
 
1.7%
Other values (53)62
35.2%
(Missing)49
27.8%
ValueCountFrequency (%)
2520771
0.6%
2577202
1.1%
2647331
0.6%
2651931
0.6%
2721571
0.6%
2787931
0.6%
2904171
0.6%
2906861
0.6%
3106061
0.6%
3153801
0.6%
ValueCountFrequency (%)
4119231
 
0.6%
3957981
 
0.6%
3939421
 
0.6%
3932561
 
0.6%
3929346
3.4%
3928841
 
0.6%
3928366
3.4%
3926821
 
0.6%
3926792
 
1.1%
3926491
 
0.6%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct44
Distinct (%)42.7%
Missing73
Missing (%)41.5%
Memory size1.5 KiB
tt11252090
13 
tt6524350
10 
tt9421868
tt5259834
tt12775836
Other values (39)
59 

Length

Max length10
Median length10
Mean length9.553398058
Min length9

Characters and Unicode

Total characters984
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)27.2%

Sample

1st rowtt8871128
2nd rowtt8871128
3rd rowtt11548668
4th rowtt13452364
5th rowtt11492320

Common Values

ValueCountFrequency (%)
tt1125209013
 
7.4%
tt652435010
 
5.7%
tt94218689
 
5.1%
tt52598346
 
3.4%
tt127758366
 
3.4%
tt134538286
 
3.4%
tt130080366
 
3.4%
tt83548123
 
1.7%
tt122568222
 
1.1%
tt93572482
 
1.1%
Other values (34)40
22.7%
(Missing)73
41.5%

Length

2022-09-05T21:37:32.920070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt1125209013
 
12.6%
tt652435010
 
9.7%
tt94218689
 
8.7%
tt52598346
 
5.8%
tt127758366
 
5.8%
tt134538286
 
5.8%
tt130080366
 
5.8%
tt83548123
 
2.9%
tt130892702
 
1.9%
tt104741342
 
1.9%
Other values (34)40
38.8%

Most occurring characters

ValueCountFrequency (%)
t206
20.9%
1111
11.3%
2109
11.1%
893
9.5%
088
8.9%
579
 
8.0%
378
 
7.9%
668
 
6.9%
460
 
6.1%
748
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number778
79.1%
Lowercase Letter206
 
20.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1111
14.3%
2109
14.0%
893
12.0%
088
11.3%
579
10.2%
378
10.0%
668
8.7%
460
7.7%
748
6.2%
944
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
t206
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common778
79.1%
Latin206
 
20.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1111
14.3%
2109
14.0%
893
12.0%
088
11.3%
579
10.2%
378
10.0%
668
8.7%
460
7.7%
748
6.2%
944
 
5.7%
Latin
ValueCountFrequency (%)
t206
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t206
20.9%
1111
11.3%
2109
11.1%
893
9.5%
088
8.9%
579
 
8.0%
378
 
7.9%
668
 
6.9%
460
 
6.1%
748
 
4.9%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct86
Distinct (%)51.2%
Missing8
Missing (%)4.5%
Memory size1.5 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/403/1008513.jpg
13 
https://static.tvmaze.com/uploads/images/medium_portrait/367/917606.jpg
 
10
https://static.tvmaze.com/uploads/images/medium_portrait/308/771883.jpg
 
9
https://static.tvmaze.com/uploads/images/medium_portrait/285/713415.jpg
 
8
https://static.tvmaze.com/uploads/images/medium_portrait/282/707479.jpg
 
6
Other values (81)
122 

Length

Max length72
Median length71
Mean length71.06547619
Min length69

Characters and Unicode

Total characters11939
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)36.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/267/668782.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713441.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713460.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713460.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/403/1008513.jpg13
 
7.4%
https://static.tvmaze.com/uploads/images/medium_portrait/367/917606.jpg10
 
5.7%
https://static.tvmaze.com/uploads/images/medium_portrait/308/771883.jpg9
 
5.1%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713415.jpg8
 
4.5%
https://static.tvmaze.com/uploads/images/medium_portrait/282/707479.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713481.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/medium_portrait/288/720292.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/medium_portrait/301/754770.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/medium_portrait/286/716265.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721792.jpg4
 
2.3%
Other values (76)94
53.4%
(Missing)8
 
4.5%

Length

2022-09-05T21:37:33.007213image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/403/1008513.jpg13
 
7.7%
https://static.tvmaze.com/uploads/images/medium_portrait/367/917606.jpg10
 
6.0%
https://static.tvmaze.com/uploads/images/medium_portrait/308/771883.jpg9
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713415.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/medium_portrait/282/707479.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713481.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/288/720292.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/301/754770.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/286/716265.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721792.jpg4
 
2.4%
Other values (76)94
56.0%

Most occurring characters

ValueCountFrequency (%)
t1176
 
9.9%
/1176
 
9.9%
m840
 
7.0%
a840
 
7.0%
p672
 
5.6%
s672
 
5.6%
i672
 
5.6%
.504
 
4.2%
o504
 
4.2%
e504
 
4.2%
Other values (22)4379
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8400
70.4%
Other Punctuation1848
 
15.5%
Decimal Number1523
 
12.8%
Connector Punctuation168
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t1176
14.0%
m840
10.0%
a840
10.0%
p672
 
8.0%
s672
 
8.0%
i672
 
8.0%
o504
 
6.0%
e504
 
6.0%
u336
 
4.0%
d336
 
4.0%
Other values (8)1848
22.0%
Decimal Number
ValueCountFrequency (%)
8212
13.9%
7210
13.8%
2188
12.3%
1184
12.1%
3160
10.5%
0159
10.4%
4114
7.5%
5108
7.1%
6108
7.1%
980
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/1176
63.6%
.504
27.3%
:168
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8400
70.4%
Common3539
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t1176
14.0%
m840
10.0%
a840
10.0%
p672
 
8.0%
s672
 
8.0%
i672
 
8.0%
o504
 
6.0%
e504
 
6.0%
u336
 
4.0%
d336
 
4.0%
Other values (8)1848
22.0%
Common
ValueCountFrequency (%)
/1176
33.2%
.504
14.2%
8212
 
6.0%
7210
 
5.9%
2188
 
5.3%
1184
 
5.2%
_168
 
4.7%
:168
 
4.7%
3160
 
4.5%
0159
 
4.5%
Other values (4)410
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII11939
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t1176
 
9.9%
/1176
 
9.9%
m840
 
7.0%
a840
 
7.0%
p672
 
5.6%
s672
 
5.6%
i672
 
5.6%
.504
 
4.2%
o504
 
4.2%
e504
 
4.2%
Other values (22)4379
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct86
Distinct (%)51.2%
Missing8
Missing (%)4.5%
Memory size1.5 KiB
https://static.tvmaze.com/uploads/images/original_untouched/403/1008513.jpg
13 
https://static.tvmaze.com/uploads/images/original_untouched/367/917606.jpg
 
10
https://static.tvmaze.com/uploads/images/original_untouched/308/771883.jpg
 
9
https://static.tvmaze.com/uploads/images/original_untouched/285/713415.jpg
 
8
https://static.tvmaze.com/uploads/images/original_untouched/282/707479.jpg
 
6
Other values (81)
122 

Length

Max length75
Median length74
Mean length74.06547619
Min length72

Characters and Unicode

Total characters12443
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)36.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/267/668782.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713441.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713460.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713460.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/403/1008513.jpg13
 
7.4%
https://static.tvmaze.com/uploads/images/original_untouched/367/917606.jpg10
 
5.7%
https://static.tvmaze.com/uploads/images/original_untouched/308/771883.jpg9
 
5.1%
https://static.tvmaze.com/uploads/images/original_untouched/285/713415.jpg8
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/282/707479.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713481.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/original_untouched/288/720292.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/original_untouched/301/754770.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/original_untouched/286/716265.jpg6
 
3.4%
https://static.tvmaze.com/uploads/images/original_untouched/288/721792.jpg4
 
2.3%
Other values (76)94
53.4%
(Missing)8
 
4.5%

Length

2022-09-05T21:37:33.097592image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/403/1008513.jpg13
 
7.7%
https://static.tvmaze.com/uploads/images/original_untouched/367/917606.jpg10
 
6.0%
https://static.tvmaze.com/uploads/images/original_untouched/308/771883.jpg9
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713415.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/original_untouched/282/707479.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/713481.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720292.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/301/754770.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716265.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/721792.jpg4
 
2.4%
Other values (76)94
56.0%

Most occurring characters

ValueCountFrequency (%)
/1176
 
9.5%
t1008
 
8.1%
a840
 
6.8%
s672
 
5.4%
i672
 
5.4%
o672
 
5.4%
p504
 
4.1%
c504
 
4.1%
.504
 
4.1%
g504
 
4.1%
Other values (23)5387
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8904
71.6%
Other Punctuation1848
 
14.9%
Decimal Number1523
 
12.2%
Connector Punctuation168
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t1008
 
11.3%
a840
 
9.4%
s672
 
7.5%
i672
 
7.5%
o672
 
7.5%
p504
 
5.7%
c504
 
5.7%
g504
 
5.7%
m504
 
5.7%
e504
 
5.7%
Other values (9)2520
28.3%
Decimal Number
ValueCountFrequency (%)
8212
13.9%
7210
13.8%
2188
12.3%
1184
12.1%
3160
10.5%
0159
10.4%
4114
7.5%
5108
7.1%
6108
7.1%
980
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/1176
63.6%
.504
27.3%
:168
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8904
71.6%
Common3539
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t1008
 
11.3%
a840
 
9.4%
s672
 
7.5%
i672
 
7.5%
o672
 
7.5%
p504
 
5.7%
c504
 
5.7%
g504
 
5.7%
m504
 
5.7%
e504
 
5.7%
Other values (9)2520
28.3%
Common
ValueCountFrequency (%)
/1176
33.2%
.504
14.2%
8212
 
6.0%
7210
 
5.9%
2188
 
5.3%
1184
 
5.2%
:168
 
4.7%
_168
 
4.7%
3160
 
4.5%
0159
 
4.5%
Other values (4)410
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII12443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/1176
 
9.5%
t1008
 
8.1%
a840
 
6.8%
s672
 
5.4%
i672
 
5.4%
o672
 
5.4%
p504
 
4.1%
c504
 
4.1%
.504
 
4.1%
g504
 
4.1%
Other values (23)5387
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct81
Distinct (%)48.8%
Missing10
Missing (%)5.7%
Memory size1.5 KiB
<p>After a family tragedy strikes, Frank Hardy, 16, and his brother Joe, 12, are forced to move from the big city to their parent's hometown of Bridgeport for the summer. Staying with their Aunt Trudy, Frank and Joe's quiet summer quickly comes to a halt when they discover their dad, detective Fenton Hardy has taken on a secret investigation. Realizing that their dad may be onto something the boys take it upon themselves to start an investigation of their own, and suddenly everyone in town is a suspect.</p>
13 
<p>Teenage friends find their lives upended by the wonders and horrors of puberty in this edgy comedy from real-life pals Nick Kroll and Andrew Goldberg.</p>
 
10
<p>As Mexican-American Tejano singer Selena comes of age and realizes her dreams, she and her family make tough choices to hold on to love and music.</p>
 
9
<p>Each episode is a parody of a popular TV show or program.</p>
 
8
<p>The Masire Brothers rule Johannesburg's criminal underworld, but a supernatural family curse and a tangled web of betrayal threaten to destroy them.</p>
 
6
Other values (76)
120 

Length

Max length1360
Median length555
Mean length356.3493976
Min length54

Characters and Unicode

Total characters59154
Distinct characters121
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)33.7%

Sample

1st row<p>A bold humorous show in which comedians fight for 50,000 rubles! Six comedians will take to the stage to "fry" each other. The top two will go to the final, and only one will take the money with them!</p>
2nd row<p><b>Plague</b> – a Comedy project about how hard it is to survive in the middle ages during the plague. This is a story about the residents of the fictional town of Hamburg, locked in a castle under quarantine. Also locked up in the castle is the Messenger William, who, in fact, brought the news of the plague.</p>
3rd row<p>Lytk-Angeles, the state of Moskvachussets, has always been a quiet town where every gang had its rightful place. The Colombians smoked plantain, the Irish sipped beer, and the Chinese ate noodles. But one day the evil Russian Communists came and brought sugar with them. They slaughtered all the street vendors of plantain, seized control of the production of matryoshka dolls (a traditional Yugoslav business) and got the whole city hooked on white powder.</p><p>This will be the last case for Eustace Lynch. Famous for his lucky tattoo, an Irish gangster comes to Lytk-Angeles from Dublin (also known as Dubna) to get rid of the Communists. At the same time, Sally Raptor, a police officer from palm beach (also known as Gelendzhik) arrives in the city with a similar task.</p><p>Zakon i Besporyadok is a parody of the films of the 80s and 90s that we watched on videotapes with one-voice voice-over as a child, and a tribute to that forever-gone era when the screen belonged entirely to evil Russians, Asian martial artists and drinking detectives in ridiculous hats. Each episode parodies one of your favorite genres: the characters don't change, but they end up in an Asian fighting game, a crime Thriller, or even a neo-noir story.</p>
4th row<p>Lytk-Angeles, the state of Moskvachussets, has always been a quiet town where every gang had its rightful place. The Colombians smoked plantain, the Irish sipped beer, and the Chinese ate noodles. But one day the evil Russian Communists came and brought sugar with them. They slaughtered all the street vendors of plantain, seized control of the production of matryoshka dolls (a traditional Yugoslav business) and got the whole city hooked on white powder.</p><p>This will be the last case for Eustace Lynch. Famous for his lucky tattoo, an Irish gangster comes to Lytk-Angeles from Dublin (also known as Dubna) to get rid of the Communists. At the same time, Sally Raptor, a police officer from palm beach (also known as Gelendzhik) arrives in the city with a similar task.</p><p>Zakon i Besporyadok is a parody of the films of the 80s and 90s that we watched on videotapes with one-voice voice-over as a child, and a tribute to that forever-gone era when the screen belonged entirely to evil Russians, Asian martial artists and drinking detectives in ridiculous hats. Each episode parodies one of your favorite genres: the characters don't change, but they end up in an Asian fighting game, a crime Thriller, or even a neo-noir story.</p>
5th row<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>

Common Values

ValueCountFrequency (%)
<p>After a family tragedy strikes, Frank Hardy, 16, and his brother Joe, 12, are forced to move from the big city to their parent's hometown of Bridgeport for the summer. Staying with their Aunt Trudy, Frank and Joe's quiet summer quickly comes to a halt when they discover their dad, detective Fenton Hardy has taken on a secret investigation. Realizing that their dad may be onto something the boys take it upon themselves to start an investigation of their own, and suddenly everyone in town is a suspect.</p>13
 
7.4%
<p>Teenage friends find their lives upended by the wonders and horrors of puberty in this edgy comedy from real-life pals Nick Kroll and Andrew Goldberg.</p>10
 
5.7%
<p>As Mexican-American Tejano singer Selena comes of age and realizes her dreams, she and her family make tough choices to hold on to love and music.</p>9
 
5.1%
<p>Each episode is a parody of a popular TV show or program.</p>8
 
4.5%
<p>The Masire Brothers rule Johannesburg's criminal underworld, but a supernatural family curse and a tangled web of betrayal threaten to destroy them.</p>6
 
3.4%
<p><b>Stillwater </b>centers on siblings Karl, Addy and Michael, who are typical kids with typical kid challenges – meaning that sometimes even the smallest things can feel insurmountable. Fortunately for these three, they have Stillwater, a wise panda, as their next-door neighbor.</p>6
 
3.4%
<p>Using cutting-edge cameras and a revolutionary editing process, <b>Earth at Night in Color</b> presents nature's previously unseen marvels with striking new clarity. Captured across six continents, from the Arctic Circle to the African grasslands, this pioneering work follows the moonlit lives of animals at night, revealing new insights and never-before-seen behaviors into some of our favorite species' nocturnal habits. The show will also introduce relatively unknown creatures who are sure to become new icons of the animal kingdom.</p>6
 
3.4%
<p>Facing disapproving parents, a knotty love life and her own inner critic, an aspiring comic ditches her cushy but unsatisfying life to pursue stand-up.</p>6
 
3.4%
<p><b>El estado contra Pablo Ibar</b> is a detailed account of the court case of more than 25 years that led to Pablo Ibar being sentenced to death for a triple homicide in Miramar, Florida. The murders were the first in U.S. history to be fully recorded on a home security camera, making the case one of the most talked about in Florida history. Pablo Ibar's case was reopened in 2016, after the Florida Supreme Court ruled that there was a lack of evidence against him.</p>6
 
3.4%
<p>Norwegian documentary series about children who grow up in different families, about their challenges, mastery and pride.</p>4
 
2.3%
Other values (71)92
52.3%
(Missing)10
 
5.7%

Length

2022-09-05T21:37:33.219696image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the460
 
4.7%
and366
 
3.8%
a320
 
3.3%
of288
 
3.0%
to269
 
2.8%
in169
 
1.7%
their150
 
1.5%
is103
 
1.1%
that86
 
0.9%
on85
 
0.9%
Other values (1914)7459
76.5%

Most occurring characters

ValueCountFrequency (%)
9579
16.2%
e5510
 
9.3%
t3700
 
6.3%
a3557
 
6.0%
o3436
 
5.8%
i3263
 
5.5%
n3243
 
5.5%
r2939
 
5.0%
s2842
 
4.8%
h2189
 
3.7%
Other values (111)18896
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter45061
76.2%
Space Separator9596
 
16.2%
Uppercase Letter1556
 
2.6%
Other Punctuation1550
 
2.6%
Math Symbol1017
 
1.7%
Decimal Number176
 
0.3%
Dash Punctuation151
 
0.3%
Open Punctuation17
 
< 0.1%
Close Punctuation17
 
< 0.1%
Format12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e5510
12.2%
t3700
 
8.2%
a3557
 
7.9%
o3436
 
7.6%
i3263
 
7.2%
n3243
 
7.2%
r2939
 
6.5%
s2842
 
6.3%
h2189
 
4.9%
l1858
 
4.1%
Other values (48)12524
27.8%
Uppercase Letter
ValueCountFrequency (%)
T181
 
11.6%
A163
 
10.5%
S155
 
10.0%
F98
 
6.3%
M93
 
6.0%
C78
 
5.0%
I77
 
4.9%
W60
 
3.9%
L60
 
3.9%
B59
 
3.8%
Other values (21)532
34.2%
Other Punctuation
ValueCountFrequency (%)
,597
38.5%
.469
30.3%
/262
16.9%
'143
 
9.2%
"39
 
2.5%
!16
 
1.0%
?12
 
0.8%
:8
 
0.5%
3
 
0.2%
;1
 
0.1%
Decimal Number
ValueCountFrequency (%)
158
33.0%
236
20.5%
023
 
13.1%
620
 
11.4%
510
 
5.7%
98
 
4.5%
37
 
4.0%
86
 
3.4%
75
 
2.8%
43
 
1.7%
Math Symbol
ValueCountFrequency (%)
<508
50.0%
>508
50.0%
+1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-133
88.1%
11
 
7.3%
7
 
4.6%
Space Separator
ValueCountFrequency (%)
9579
99.8%
 17
 
0.2%
Open Punctuation
ValueCountFrequency (%)
(17
100.0%
Close Punctuation
ValueCountFrequency (%)
)17
100.0%
Format
ValueCountFrequency (%)
12
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin46229
78.2%
Common12537
 
21.2%
Cyrillic388
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5510
11.9%
t3700
 
8.0%
a3557
 
7.7%
o3436
 
7.4%
i3263
 
7.1%
n3243
 
7.0%
r2939
 
6.4%
s2842
 
6.1%
h2189
 
4.7%
l1858
 
4.0%
Other values (45)13692
29.6%
Cyrillic
ValueCountFrequency (%)
е38
 
9.8%
и38
 
9.8%
т37
 
9.5%
о35
 
9.0%
с25
 
6.4%
н24
 
6.2%
а24
 
6.2%
м21
 
5.4%
в16
 
4.1%
р15
 
3.9%
Other values (24)115
29.6%
Common
ValueCountFrequency (%)
9579
76.4%
,597
 
4.8%
<508
 
4.1%
>508
 
4.1%
.469
 
3.7%
/262
 
2.1%
'143
 
1.1%
-133
 
1.1%
158
 
0.5%
"39
 
0.3%
Other values (22)241
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII58708
99.2%
Cyrillic388
 
0.7%
Punctuation34
 
0.1%
None24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9579
16.3%
e5510
 
9.4%
t3700
 
6.3%
a3557
 
6.1%
o3436
 
5.9%
i3263
 
5.6%
n3243
 
5.5%
r2939
 
5.0%
s2842
 
4.8%
h2189
 
3.7%
Other values (68)18450
31.4%
Cyrillic
ValueCountFrequency (%)
е38
 
9.8%
и38
 
9.8%
т37
 
9.5%
о35
 
9.0%
с25
 
6.4%
н24
 
6.2%
а24
 
6.2%
м21
 
5.4%
в16
 
4.1%
р15
 
3.9%
Other values (24)115
29.6%
None
ValueCountFrequency (%)
 17
70.8%
Í3
 
12.5%
ø2
 
8.3%
ä2
 
8.3%
Punctuation
ValueCountFrequency (%)
12
35.3%
11
32.4%
7
20.6%
3
 
8.8%
1
 
2.9%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct91
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1638495803
Minimum1604587145
Maximum1662418845
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2022-09-05T21:37:33.338266image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1604587145
5-th percentile1607278887
Q11620260577
median1646932332
Q31653904806
95-th percentile1661808482
Maximum1662418845
Range57831700
Interquartile range (IQR)33644229.5

Descriptive statistics

Standard deviation19581678.9
Coefficient of variation (CV)0.01195100949
Kurtosis-1.368964809
Mean1638495803
Median Absolute Deviation (MAD)14429700.5
Skewness-0.4139991575
Sum2.883752614 × 1011
Variance3.834421485 × 1014
MonotonicityNot monotonic
2022-09-05T21:37:33.460800image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165345093913
 
7.4%
166136203210
 
5.7%
16202605779
 
5.1%
16072788878
 
4.5%
16253050826
 
3.4%
16618084826
 
3.4%
16085889856
 
3.4%
16075748986
 
3.4%
16478498636
 
3.4%
16235338634
 
2.3%
Other values (81)102
58.0%
ValueCountFrequency (%)
16045871451
 
0.6%
16071040921
 
0.6%
16072788878
4.5%
16075748986
3.4%
16078871751
 
0.6%
16081468711
 
0.6%
16084019621
 
0.6%
16085889856
3.4%
16094684031
 
0.6%
16095364481
 
0.6%
ValueCountFrequency (%)
16624188451
 
0.6%
16622799521
 
0.6%
16622629611
 
0.6%
16621513691
 
0.6%
16621074082
 
1.1%
16620118651
 
0.6%
16618084826
3.4%
16616981471
 
0.6%
16613636441
 
0.6%
166136203210
5.7%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct91
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
https://api.tvmaze.com/shows/45235
 
13
https://api.tvmaze.com/shows/28757
 
10
https://api.tvmaze.com/shows/40019
 
9
https://api.tvmaze.com/shows/49738
 
8
https://api.tvmaze.com/shows/49940
 
6
Other values (86)
130 

Length

Max length34
Median length34
Mean length33.98863636
Min length33

Characters and Unicode

Total characters5982
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)37.5%

Sample

1st rowhttps://api.tvmaze.com/shows/48288
2nd rowhttps://api.tvmaze.com/shows/48402
3rd rowhttps://api.tvmaze.com/shows/52118
4th rowhttps://api.tvmaze.com/shows/52118
5th rowhttps://api.tvmaze.com/shows/52198

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/4523513
 
7.4%
https://api.tvmaze.com/shows/2875710
 
5.7%
https://api.tvmaze.com/shows/400199
 
5.1%
https://api.tvmaze.com/shows/497388
 
4.5%
https://api.tvmaze.com/shows/499406
 
3.4%
https://api.tvmaze.com/shows/519146
 
3.4%
https://api.tvmaze.com/shows/521246
 
3.4%
https://api.tvmaze.com/shows/523206
 
3.4%
https://api.tvmaze.com/shows/504636
 
3.4%
https://api.tvmaze.com/shows/524154
 
2.3%
Other values (81)102
58.0%

Length

2022-09-05T21:37:33.560406image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/4523513
 
7.4%
https://api.tvmaze.com/shows/2875710
 
5.7%
https://api.tvmaze.com/shows/400199
 
5.1%
https://api.tvmaze.com/shows/497388
 
4.5%
https://api.tvmaze.com/shows/499406
 
3.4%
https://api.tvmaze.com/shows/519146
 
3.4%
https://api.tvmaze.com/shows/521246
 
3.4%
https://api.tvmaze.com/shows/523206
 
3.4%
https://api.tvmaze.com/shows/504636
 
3.4%
https://api.tvmaze.com/shows/594954
 
2.3%
Other values (81)102
58.0%

Most occurring characters

ValueCountFrequency (%)
/704
 
11.8%
s528
 
8.8%
t528
 
8.8%
h352
 
5.9%
p352
 
5.9%
a352
 
5.9%
o352
 
5.9%
.352
 
5.9%
m352
 
5.9%
e176
 
2.9%
Other values (16)1934
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3872
64.7%
Other Punctuation1232
 
20.6%
Decimal Number878
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s528
13.6%
t528
13.6%
h352
9.1%
p352
9.1%
a352
9.1%
o352
9.1%
m352
9.1%
e176
 
4.5%
w176
 
4.5%
c176
 
4.5%
Other values (3)528
13.6%
Decimal Number
ValueCountFrequency (%)
5162
18.5%
4129
14.7%
1111
12.6%
297
11.0%
083
9.5%
979
9.0%
369
7.9%
652
 
5.9%
750
 
5.7%
846
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/704
57.1%
.352
28.6%
:176
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3872
64.7%
Common2110
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/704
33.4%
.352
16.7%
:176
 
8.3%
5162
 
7.7%
4129
 
6.1%
1111
 
5.3%
297
 
4.6%
083
 
3.9%
979
 
3.7%
369
 
3.3%
Other values (3)148
 
7.0%
Latin
ValueCountFrequency (%)
s528
13.6%
t528
13.6%
h352
9.1%
p352
9.1%
a352
9.1%
o352
9.1%
m352
9.1%
e176
 
4.5%
w176
 
4.5%
c176
 
4.5%
Other values (3)528
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII5982
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/704
 
11.8%
s528
 
8.8%
t528
 
8.8%
h352
 
5.9%
p352
 
5.9%
a352
 
5.9%
o352
 
5.9%
.352
 
5.9%
m352
 
5.9%
e176
 
2.9%
Other values (16)1934
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct91
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
https://api.tvmaze.com/episodes/2297925
 
13
https://api.tvmaze.com/episodes/2203062
 
10
https://api.tvmaze.com/episodes/2083573
 
9
https://api.tvmaze.com/episodes/1960854
 
8
https://api.tvmaze.com/episodes/2072167
 
6
Other values (86)
130 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6864
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)37.5%

Sample

1st rowhttps://api.tvmaze.com/episodes/2362860
2nd rowhttps://api.tvmaze.com/episodes/1961005
3rd rowhttps://api.tvmaze.com/episodes/1976572
4th rowhttps://api.tvmaze.com/episodes/1976572
5th rowhttps://api.tvmaze.com/episodes/1986873

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/229792513
 
7.4%
https://api.tvmaze.com/episodes/220306210
 
5.7%
https://api.tvmaze.com/episodes/20835739
 
5.1%
https://api.tvmaze.com/episodes/19608548
 
4.5%
https://api.tvmaze.com/episodes/20721676
 
3.4%
https://api.tvmaze.com/episodes/19697246
 
3.4%
https://api.tvmaze.com/episodes/19792396
 
3.4%
https://api.tvmaze.com/episodes/19835926
 
3.4%
https://api.tvmaze.com/episodes/22990106
 
3.4%
https://api.tvmaze.com/episodes/19853294
 
2.3%
Other values (81)102
58.0%

Length

2022-09-05T21:37:33.653153image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/229792513
 
7.4%
https://api.tvmaze.com/episodes/220306210
 
5.7%
https://api.tvmaze.com/episodes/20835739
 
5.1%
https://api.tvmaze.com/episodes/19608548
 
4.5%
https://api.tvmaze.com/episodes/20721676
 
3.4%
https://api.tvmaze.com/episodes/19697246
 
3.4%
https://api.tvmaze.com/episodes/19792396
 
3.4%
https://api.tvmaze.com/episodes/19835926
 
3.4%
https://api.tvmaze.com/episodes/22990106
 
3.4%
https://api.tvmaze.com/episodes/22369804
 
2.3%
Other values (81)102
58.0%

Most occurring characters

ValueCountFrequency (%)
/704
 
10.3%
p528
 
7.7%
s528
 
7.7%
e528
 
7.7%
t528
 
7.7%
o352
 
5.1%
a352
 
5.1%
i352
 
5.1%
.352
 
5.1%
m352
 
5.1%
Other values (16)2288
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4400
64.1%
Other Punctuation1232
 
17.9%
Decimal Number1232
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p528
12.0%
s528
12.0%
e528
12.0%
t528
12.0%
o352
8.0%
a352
8.0%
i352
8.0%
m352
8.0%
h176
 
4.0%
d176
 
4.0%
Other values (3)528
12.0%
Decimal Number
ValueCountFrequency (%)
2250
20.3%
9187
15.2%
1126
10.2%
7110
8.9%
0110
8.9%
3106
8.6%
598
 
8.0%
890
 
7.3%
684
 
6.8%
471
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/704
57.1%
.352
28.6%
:176
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4400
64.1%
Common2464
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/704
28.6%
.352
14.3%
2250
 
10.1%
9187
 
7.6%
:176
 
7.1%
1126
 
5.1%
7110
 
4.5%
0110
 
4.5%
3106
 
4.3%
598
 
4.0%
Other values (3)245
 
9.9%
Latin
ValueCountFrequency (%)
p528
12.0%
s528
12.0%
e528
12.0%
t528
12.0%
o352
8.0%
a352
8.0%
i352
8.0%
m352
8.0%
h176
 
4.0%
d176
 
4.0%
Other values (3)528
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/704
 
10.3%
p528
 
7.7%
s528
 
7.7%
e528
 
7.7%
t528
 
7.7%
o352
 
5.1%
a352
 
5.1%
i352
 
5.1%
.352
 
5.1%
m352
 
5.1%
Other values (16)2288
33.3%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)21.9%
Missing103
Missing (%)58.5%
Memory size1.5 KiB
United States
24 
China
10 
Norway
10 
Spain
Russian Federation
Other values (11)
15 

Length

Max length18
Median length14
Mean length9.575342466
Min length5

Characters and Unicode

Total characters699
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)11.0%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowRussian Federation
5th rowChina

Common Values

ValueCountFrequency (%)
United States24
 
13.6%
China10
 
5.7%
Norway10
 
5.7%
Spain9
 
5.1%
Russian Federation5
 
2.8%
Korea, Republic of3
 
1.7%
Turkey2
 
1.1%
Belgium2
 
1.1%
Netherlands1
 
0.6%
Brazil1
 
0.6%
Other values (6)6
 
3.4%
(Missing)103
58.5%

Length

2022-09-05T21:37:33.750547image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united25
22.9%
states24
22.0%
china10
 
9.2%
norway10
 
9.2%
spain9
 
8.3%
russian5
 
4.6%
federation5
 
4.6%
korea3
 
2.8%
republic3
 
2.8%
of3
 
2.8%
Other values (10)12
11.0%

Most occurring characters

ValueCountFrequency (%)
t80
11.4%
a76
10.9%
e72
 
10.3%
i62
 
8.9%
n60
 
8.6%
36
 
5.2%
s35
 
5.0%
d34
 
4.9%
S33
 
4.7%
U25
 
3.6%
Other values (27)186
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter554
79.3%
Uppercase Letter106
 
15.2%
Space Separator36
 
5.2%
Other Punctuation3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t80
14.4%
a76
13.7%
e72
13.0%
i62
11.2%
n60
10.8%
s35
6.3%
d34
6.1%
r24
 
4.3%
o23
 
4.2%
p13
 
2.3%
Other values (12)75
13.5%
Uppercase Letter
ValueCountFrequency (%)
S33
31.1%
U25
23.6%
N11
 
10.4%
C11
 
10.4%
R8
 
7.5%
F5
 
4.7%
K4
 
3.8%
B3
 
2.8%
T2
 
1.9%
P1
 
0.9%
Other values (3)3
 
2.8%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin660
94.4%
Common39
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t80
12.1%
a76
11.5%
e72
10.9%
i62
 
9.4%
n60
 
9.1%
s35
 
5.3%
d34
 
5.2%
S33
 
5.0%
U25
 
3.8%
r24
 
3.6%
Other values (25)159
24.1%
Common
ValueCountFrequency (%)
36
92.3%
,3
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t80
11.4%
a76
10.9%
e72
 
10.3%
i62
 
8.9%
n60
 
8.6%
36
 
5.2%
s35
 
5.0%
d34
 
4.9%
S33
 
4.7%
U25
 
3.6%
Other values (27)186
26.6%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)21.9%
Missing103
Missing (%)58.5%
Memory size1.5 KiB
US
24 
CN
10 
NO
10 
ES
RU
Other values (11)
15 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters146
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)11.0%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowRU
5th rowCN

Common Values

ValueCountFrequency (%)
US24
 
13.6%
CN10
 
5.7%
NO10
 
5.7%
ES9
 
5.1%
RU5
 
2.8%
KR3
 
1.7%
TR2
 
1.1%
BE2
 
1.1%
NL1
 
0.6%
BR1
 
0.6%
Other values (6)6
 
3.4%
(Missing)103
58.5%

Length

2022-09-05T21:37:33.834952image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
us24
32.9%
cn10
13.7%
no10
13.7%
es9
 
12.3%
ru5
 
6.8%
kr3
 
4.1%
tr2
 
2.7%
be2
 
2.7%
nl1
 
1.4%
br1
 
1.4%
Other values (6)6
 
8.2%

Most occurring characters

ValueCountFrequency (%)
S33
22.6%
U29
19.9%
N22
15.1%
E12
 
8.2%
C11
 
7.5%
R11
 
7.5%
O10
 
6.8%
B4
 
2.7%
T3
 
2.1%
K3
 
2.1%
Other values (7)8
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter146
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S33
22.6%
U29
19.9%
N22
15.1%
E12
 
8.2%
C11
 
7.5%
R11
 
7.5%
O10
 
6.8%
B4
 
2.7%
T3
 
2.1%
K3
 
2.1%
Other values (7)8
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Latin146
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S33
22.6%
U29
19.9%
N22
15.1%
E12
 
8.2%
C11
 
7.5%
R11
 
7.5%
O10
 
6.8%
B4
 
2.7%
T3
 
2.1%
K3
 
2.1%
Other values (7)8
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S33
22.6%
U29
19.9%
N22
15.1%
E12
 
8.2%
C11
 
7.5%
R11
 
7.5%
O10
 
6.8%
B4
 
2.7%
T3
 
2.1%
K3
 
2.1%
Other values (7)8
 
5.5%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)21.9%
Missing103
Missing (%)58.5%
Memory size1.5 KiB
America/New_York
24 
Asia/Shanghai
10 
Europe/Oslo
10 
Europe/Madrid
Asia/Kamchatka
Other values (11)
15 

Length

Max length16
Median length15
Mean length13.83561644
Min length10

Characters and Unicode

Total characters1010
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)11.0%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
America/New_York24
 
13.6%
Asia/Shanghai10
 
5.7%
Europe/Oslo10
 
5.7%
Europe/Madrid9
 
5.1%
Asia/Kamchatka5
 
2.8%
Asia/Seoul3
 
1.7%
Europe/Istanbul2
 
1.1%
Europe/Brussels2
 
1.1%
Europe/Amsterdam1
 
0.6%
America/Noronha1
 
0.6%
Other values (6)6
 
3.4%
(Missing)103
58.5%

Length

2022-09-05T21:37:33.924909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
america/new_york24
32.9%
asia/shanghai10
13.7%
europe/oslo10
13.7%
europe/madrid9
 
12.3%
asia/kamchatka5
 
6.8%
asia/seoul3
 
4.1%
europe/istanbul2
 
2.7%
europe/brussels2
 
2.7%
europe/amsterdam1
 
1.4%
america/noronha1
 
1.4%
Other values (6)6
 
8.2%

Most occurring characters

ValueCountFrequency (%)
a98
 
9.7%
r90
 
8.9%
e84
 
8.3%
/73
 
7.2%
o72
 
7.1%
i68
 
6.7%
A47
 
4.7%
s41
 
4.1%
u35
 
3.5%
m33
 
3.3%
Other values (27)369
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter743
73.6%
Uppercase Letter170
 
16.8%
Other Punctuation73
 
7.2%
Connector Punctuation24
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a98
13.2%
r90
12.1%
e84
11.3%
o72
9.7%
i68
9.2%
s41
 
5.5%
u35
 
4.7%
m33
 
4.4%
c31
 
4.2%
k31
 
4.2%
Other values (12)160
21.5%
Uppercase Letter
ValueCountFrequency (%)
A47
27.6%
E27
15.9%
N25
14.7%
Y24
14.1%
S13
 
7.6%
O10
 
5.9%
M9
 
5.3%
K6
 
3.5%
B3
 
1.8%
I2
 
1.2%
Other values (3)4
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/73
100.0%
Connector Punctuation
ValueCountFrequency (%)
_24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin913
90.4%
Common97
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a98
 
10.7%
r90
 
9.9%
e84
 
9.2%
o72
 
7.9%
i68
 
7.4%
A47
 
5.1%
s41
 
4.5%
u35
 
3.8%
m33
 
3.6%
c31
 
3.4%
Other values (25)314
34.4%
Common
ValueCountFrequency (%)
/73
75.3%
_24
 
24.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1010
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a98
 
9.7%
r90
 
8.9%
e84
 
8.3%
/73
 
7.2%
o72
 
7.1%
i68
 
6.7%
A47
 
4.7%
s41
 
4.1%
u35
 
3.5%
m33
 
3.3%
Other values (27)369
36.5%

image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct98
Distinct (%)100.0%
Missing78
Missing (%)44.3%
Memory size1.5 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/286/716279.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/286/716277.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/286/716712.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/286/716709.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/286/716472.jpg
 
1
Other values (93)
93 

Length

Max length73
Median length72
Mean length72.03061224
Min length72

Characters and Unicode

Total characters7059
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719797.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/285/714185.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726338.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/716428.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/716537.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/286/716279.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716277.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716712.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716709.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716472.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/293/732801.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716262.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716261.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716260.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716259.jpg1
 
0.6%
Other values (88)88
50.0%
(Missing)78
44.3%

Length

2022-09-05T21:37:34.009048image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/286/716279.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716245.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714185.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726338.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716428.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716537.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716538.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/282/707166.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/283/708518.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718029.jpg1
 
1.0%
Other values (88)88
89.8%

Most occurring characters

ValueCountFrequency (%)
/686
 
9.7%
a588
 
8.3%
m490
 
6.9%
s490
 
6.9%
t490
 
6.9%
p392
 
5.6%
e392
 
5.6%
.294
 
4.2%
d294
 
4.2%
c294
 
4.2%
Other values (22)2649
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4998
70.8%
Other Punctuation1078
 
15.3%
Decimal Number885
 
12.5%
Connector Punctuation98
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a588
11.8%
m490
9.8%
s490
9.8%
t490
9.8%
p392
 
7.8%
e392
 
7.8%
d294
 
5.9%
c294
 
5.9%
i294
 
5.9%
g196
 
3.9%
Other values (8)1078
21.6%
Decimal Number
ValueCountFrequency (%)
2163
18.4%
6163
18.4%
7131
14.8%
1123
13.9%
8119
13.4%
349
 
5.5%
044
 
5.0%
533
 
3.7%
932
 
3.6%
428
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/686
63.6%
.294
27.3%
:98
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4998
70.8%
Common2061
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a588
11.8%
m490
9.8%
s490
9.8%
t490
9.8%
p392
 
7.8%
e392
 
7.8%
d294
 
5.9%
c294
 
5.9%
i294
 
5.9%
g196
 
3.9%
Other values (8)1078
21.6%
Common
ValueCountFrequency (%)
/686
33.3%
.294
14.3%
2163
 
7.9%
6163
 
7.9%
7131
 
6.4%
1123
 
6.0%
8119
 
5.8%
_98
 
4.8%
:98
 
4.8%
349
 
2.4%
Other values (4)137
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII7059
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/686
 
9.7%
a588
 
8.3%
m490
 
6.9%
s490
 
6.9%
t490
 
6.9%
p392
 
5.6%
e392
 
5.6%
.294
 
4.2%
d294
 
4.2%
c294
 
4.2%
Other values (22)2649
37.5%

image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct98
Distinct (%)100.0%
Missing78
Missing (%)44.3%
Memory size1.5 KiB
https://static.tvmaze.com/uploads/images/original_untouched/286/716279.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/286/716277.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/286/716712.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/286/716709.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/286/716472.jpg
 
1
Other values (93)
93 

Length

Max length75
Median length74
Mean length74.03061224
Min length74

Characters and Unicode

Total characters7255
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719797.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/714185.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726338.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/716428.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/716537.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/286/716279.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716277.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716712.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716709.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716472.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/293/732801.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716262.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716261.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716260.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/286/716259.jpg1
 
0.6%
Other values (88)88
50.0%
(Missing)78
44.3%

Length

2022-09-05T21:37:34.087239image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/286/716279.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/286/716245.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/714185.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726338.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/286/716428.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/286/716537.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/286/716538.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/282/707166.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/283/708518.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/718029.jpg1
 
1.0%
Other values (88)88
89.8%

Most occurring characters

ValueCountFrequency (%)
/686
 
9.5%
t588
 
8.1%
a490
 
6.8%
s392
 
5.4%
i392
 
5.4%
o392
 
5.4%
p294
 
4.1%
c294
 
4.1%
.294
 
4.1%
g294
 
4.1%
Other values (23)3139
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5194
71.6%
Other Punctuation1078
 
14.9%
Decimal Number885
 
12.2%
Connector Punctuation98
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t588
 
11.3%
a490
 
9.4%
s392
 
7.5%
i392
 
7.5%
o392
 
7.5%
p294
 
5.7%
c294
 
5.7%
g294
 
5.7%
m294
 
5.7%
e294
 
5.7%
Other values (9)1470
28.3%
Decimal Number
ValueCountFrequency (%)
2163
18.4%
6163
18.4%
7131
14.8%
1123
13.9%
8119
13.4%
349
 
5.5%
044
 
5.0%
533
 
3.7%
932
 
3.6%
428
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/686
63.6%
.294
27.3%
:98
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5194
71.6%
Common2061
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t588
 
11.3%
a490
 
9.4%
s392
 
7.5%
i392
 
7.5%
o392
 
7.5%
p294
 
5.7%
c294
 
5.7%
g294
 
5.7%
m294
 
5.7%
e294
 
5.7%
Other values (9)1470
28.3%
Common
ValueCountFrequency (%)
/686
33.3%
.294
14.3%
2163
 
7.9%
6163
 
7.9%
7131
 
6.4%
1123
 
6.0%
8119
 
5.8%
:98
 
4.8%
_98
 
4.8%
349
 
2.4%
Other values (4)137
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII7255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/686
 
9.5%
t588
 
8.1%
a490
 
6.8%
s392
 
5.4%
i392
 
5.4%
o392
 
5.4%
p294
 
4.1%
c294
 
4.1%
.294
 
4.1%
g294
 
4.1%
Other values (23)3139
43.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)37.5%
Missing160
Missing (%)90.9%
Memory size1.5 KiB
https://api.tvmaze.com/episodes/2378189
10 
https://api.tvmaze.com/episodes/2383839
https://api.tvmaze.com/episodes/2384253
 
1
https://api.tvmaze.com/episodes/2376729
 
1
https://api.tvmaze.com/episodes/2280414
 
1

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters624
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)25.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2384253
2nd rowhttps://api.tvmaze.com/episodes/2376729
3rd rowhttps://api.tvmaze.com/episodes/2280414
4th rowhttps://api.tvmaze.com/episodes/2378189
5th rowhttps://api.tvmaze.com/episodes/2378189

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/237818910
 
5.7%
https://api.tvmaze.com/episodes/23838392
 
1.1%
https://api.tvmaze.com/episodes/23842531
 
0.6%
https://api.tvmaze.com/episodes/23767291
 
0.6%
https://api.tvmaze.com/episodes/22804141
 
0.6%
https://api.tvmaze.com/episodes/23542551
 
0.6%
(Missing)160
90.9%

Length

2022-09-05T21:37:34.168551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:34.262337image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/237818910
62.5%
https://api.tvmaze.com/episodes/23838392
 
12.5%
https://api.tvmaze.com/episodes/23842531
 
6.2%
https://api.tvmaze.com/episodes/23767291
 
6.2%
https://api.tvmaze.com/episodes/22804141
 
6.2%
https://api.tvmaze.com/episodes/23542551
 
6.2%

Most occurring characters

ValueCountFrequency (%)
/64
 
10.3%
p48
 
7.7%
s48
 
7.7%
e48
 
7.7%
t48
 
7.7%
a32
 
5.1%
i32
 
5.1%
.32
 
5.1%
m32
 
5.1%
o32
 
5.1%
Other values (16)208
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter400
64.1%
Other Punctuation112
 
17.9%
Decimal Number112
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p48
12.0%
s48
12.0%
e48
12.0%
t48
12.0%
a32
8.0%
i32
8.0%
m32
8.0%
o32
8.0%
h16
 
4.0%
d16
 
4.0%
Other values (3)48
12.0%
Decimal Number
ValueCountFrequency (%)
826
23.2%
320
17.9%
220
17.9%
913
11.6%
712
10.7%
111
9.8%
44
 
3.6%
54
 
3.6%
61
 
0.9%
01
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/64
57.1%
.32
28.6%
:16
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin400
64.1%
Common224
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/64
28.6%
.32
14.3%
826
11.6%
320
 
8.9%
220
 
8.9%
:16
 
7.1%
913
 
5.8%
712
 
5.4%
111
 
4.9%
44
 
1.8%
Other values (3)6
 
2.7%
Latin
ValueCountFrequency (%)
p48
12.0%
s48
12.0%
e48
12.0%
t48
12.0%
a32
8.0%
i32
8.0%
m32
8.0%
o32
8.0%
h16
 
4.0%
d16
 
4.0%
Other values (3)48
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/64
 
10.3%
p48
 
7.7%
s48
 
7.7%
e48
 
7.7%
t48
 
7.7%
a32
 
5.1%
i32
 
5.1%
.32
 
5.1%
m32
 
5.1%
o32
 
5.1%
Other values (16)208
33.3%

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5
Distinct (%)45.5%
Missing165
Missing (%)93.8%
Memory size1.5 KiB
78.0
41.0
339.0
276.0
374.0

Length

Max length5
Median length4
Mean length4.454545455
Min length4

Characters and Unicode

Total characters49
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st row339.0
2nd row339.0
3rd row276.0
4th row276.0
5th row78.0

Common Values

ValueCountFrequency (%)
78.03
 
1.7%
41.03
 
1.7%
339.02
 
1.1%
276.02
 
1.1%
374.01
 
0.6%
(Missing)165
93.8%

Length

2022-09-05T21:37:34.347608image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:34.434848image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
78.03
27.3%
41.03
27.3%
339.02
18.2%
276.02
18.2%
374.01
 
9.1%

Most occurring characters

ValueCountFrequency (%)
.11
22.4%
011
22.4%
76
12.2%
35
10.2%
44
 
8.2%
83
 
6.1%
13
 
6.1%
92
 
4.1%
22
 
4.1%
62
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number38
77.6%
Other Punctuation11
 
22.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
011
28.9%
76
15.8%
35
13.2%
44
 
10.5%
83
 
7.9%
13
 
7.9%
92
 
5.3%
22
 
5.3%
62
 
5.3%
Other Punctuation
ValueCountFrequency (%)
.11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common49
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.11
22.4%
011
22.4%
76
12.2%
35
10.2%
44
 
8.2%
83
 
6.1%
13
 
6.1%
92
 
4.1%
22
 
4.1%
62
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII49
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.11
22.4%
011
22.4%
76
12.2%
35
10.2%
44
 
8.2%
83
 
6.1%
13
 
6.1%
92
 
4.1%
22
 
4.1%
62
 
4.1%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)45.5%
Missing165
Missing (%)93.8%
Memory size1.5 KiB
Disney Channel
E4
TV 2
Hunan TV
TV Globo

Length

Max length14
Median length8
Mean length7.272727273
Min length2

Characters and Unicode

Total characters80
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st rowTV 2
2nd rowTV 2
3rd rowHunan TV
4th rowHunan TV
5th rowDisney Channel

Common Values

ValueCountFrequency (%)
Disney Channel3
 
1.7%
E43
 
1.7%
TV 22
 
1.1%
Hunan TV2
 
1.1%
TV Globo1
 
0.6%
(Missing)165
93.8%

Length

2022-09-05T21:37:34.518959image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:34.610995image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tv5
26.3%
disney3
15.8%
channel3
15.8%
e43
15.8%
22
 
10.5%
hunan2
 
10.5%
globo1
 
5.3%

Most occurring characters

ValueCountFrequency (%)
n13
16.2%
8
 
10.0%
e6
 
7.5%
V5
 
6.2%
T5
 
6.2%
a5
 
6.2%
l4
 
5.0%
i3
 
3.8%
43
 
3.8%
E3
 
3.8%
Other values (11)25
31.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter45
56.2%
Uppercase Letter22
27.5%
Space Separator8
 
10.0%
Decimal Number5
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n13
28.9%
e6
13.3%
a5
 
11.1%
l4
 
8.9%
i3
 
6.7%
h3
 
6.7%
y3
 
6.7%
s3
 
6.7%
u2
 
4.4%
o2
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
V5
22.7%
T5
22.7%
E3
13.6%
D3
13.6%
C3
13.6%
H2
 
9.1%
G1
 
4.5%
Decimal Number
ValueCountFrequency (%)
43
60.0%
22
40.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin67
83.8%
Common13
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n13
19.4%
e6
 
9.0%
V5
 
7.5%
T5
 
7.5%
a5
 
7.5%
l4
 
6.0%
i3
 
4.5%
E3
 
4.5%
D3
 
4.5%
h3
 
4.5%
Other values (8)17
25.4%
Common
ValueCountFrequency (%)
8
61.5%
43
 
23.1%
22
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n13
16.2%
8
 
10.0%
e6
 
7.5%
V5
 
6.2%
T5
 
6.2%
a5
 
6.2%
l4
 
5.0%
i3
 
3.8%
43
 
3.8%
E3
 
3.8%
Other values (11)25
31.2%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)45.5%
Missing165
Missing (%)93.8%
Memory size1.5 KiB
United States
United Kingdom
Norway
China
Brazil

Length

Max length14
Median length13
Mean length9.909090909
Min length5

Characters and Unicode

Total characters109
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st rowNorway
2nd rowNorway
3rd rowChina
4th rowChina
5th rowUnited States

Common Values

ValueCountFrequency (%)
United States3
 
1.7%
United Kingdom3
 
1.7%
Norway2
 
1.1%
China2
 
1.1%
Brazil1
 
0.6%
(Missing)165
93.8%

Length

2022-09-05T21:37:34.699884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:34.789802image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
united6
35.3%
states3
17.6%
kingdom3
17.6%
norway2
 
11.8%
china2
 
11.8%
brazil1
 
5.9%

Most occurring characters

ValueCountFrequency (%)
i12
11.0%
t12
11.0%
n11
 
10.1%
e9
 
8.3%
d9
 
8.3%
a8
 
7.3%
U6
 
5.5%
6
 
5.5%
o5
 
4.6%
r3
 
2.8%
Other values (13)28
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter86
78.9%
Uppercase Letter17
 
15.6%
Space Separator6
 
5.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i12
14.0%
t12
14.0%
n11
12.8%
e9
10.5%
d9
10.5%
a8
9.3%
o5
5.8%
r3
 
3.5%
m3
 
3.5%
g3
 
3.5%
Other values (6)11
12.8%
Uppercase Letter
ValueCountFrequency (%)
U6
35.3%
K3
17.6%
S3
17.6%
N2
 
11.8%
C2
 
11.8%
B1
 
5.9%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin103
94.5%
Common6
 
5.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i12
11.7%
t12
11.7%
n11
10.7%
e9
 
8.7%
d9
 
8.7%
a8
 
7.8%
U6
 
5.8%
o5
 
4.9%
r3
 
2.9%
m3
 
2.9%
Other values (12)25
24.3%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i12
11.0%
t12
11.0%
n11
 
10.1%
e9
 
8.3%
d9
 
8.3%
a8
 
7.3%
U6
 
5.5%
6
 
5.5%
o5
 
4.6%
r3
 
2.8%
Other values (13)28
25.7%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)45.5%
Missing165
Missing (%)93.8%
Memory size1.5 KiB
US
GB
NO
CN
BR

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters22
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st rowNO
2nd rowNO
3rd rowCN
4th rowCN
5th rowUS

Common Values

ValueCountFrequency (%)
US3
 
1.7%
GB3
 
1.7%
NO2
 
1.1%
CN2
 
1.1%
BR1
 
0.6%
(Missing)165
93.8%

Length

2022-09-05T21:37:34.874152image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:34.962395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
us3
27.3%
gb3
27.3%
no2
18.2%
cn2
18.2%
br1
 
9.1%

Most occurring characters

ValueCountFrequency (%)
B4
18.2%
N4
18.2%
U3
13.6%
S3
13.6%
G3
13.6%
O2
9.1%
C2
9.1%
R1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter22
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B4
18.2%
N4
18.2%
U3
13.6%
S3
13.6%
G3
13.6%
O2
9.1%
C2
9.1%
R1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin22
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
B4
18.2%
N4
18.2%
U3
13.6%
S3
13.6%
G3
13.6%
O2
9.1%
C2
9.1%
R1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B4
18.2%
N4
18.2%
U3
13.6%
S3
13.6%
G3
13.6%
O2
9.1%
C2
9.1%
R1
 
4.5%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)45.5%
Missing165
Missing (%)93.8%
Memory size1.5 KiB
America/New_York
Europe/London
Europe/Oslo
Asia/Shanghai
America/Noronha

Length

Max length16
Median length15
Mean length13.63636364
Min length11

Characters and Unicode

Total characters150
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st rowEurope/Oslo
2nd rowEurope/Oslo
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
America/New_York3
 
1.7%
Europe/London3
 
1.7%
Europe/Oslo2
 
1.1%
Asia/Shanghai2
 
1.1%
America/Noronha1
 
0.6%
(Missing)165
93.8%

Length

2022-09-05T21:37:35.044873image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:35.136248image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
america/new_york3
27.3%
europe/london3
27.3%
europe/oslo2
18.2%
asia/shanghai2
18.2%
america/noronha1
 
9.1%

Most occurring characters

ValueCountFrequency (%)
o18
 
12.0%
r13
 
8.7%
e12
 
8.0%
a11
 
7.3%
/11
 
7.3%
n9
 
6.0%
i8
 
5.3%
A6
 
4.0%
u5
 
3.3%
E5
 
3.3%
Other values (16)52
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter111
74.0%
Uppercase Letter25
 
16.7%
Other Punctuation11
 
7.3%
Connector Punctuation3
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o18
16.2%
r13
11.7%
e12
10.8%
a11
9.9%
n9
8.1%
i8
 
7.2%
u5
 
4.5%
p5
 
4.5%
h5
 
4.5%
s4
 
3.6%
Other values (7)21
18.9%
Uppercase Letter
ValueCountFrequency (%)
A6
24.0%
E5
20.0%
N4
16.0%
L3
12.0%
Y3
12.0%
O2
 
8.0%
S2
 
8.0%
Other Punctuation
ValueCountFrequency (%)
/11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin136
90.7%
Common14
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o18
13.2%
r13
 
9.6%
e12
 
8.8%
a11
 
8.1%
n9
 
6.6%
i8
 
5.9%
A6
 
4.4%
u5
 
3.7%
E5
 
3.7%
p5
 
3.7%
Other values (14)44
32.4%
Common
ValueCountFrequency (%)
/11
78.6%
_3
 
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o18
 
12.0%
r13
 
8.7%
e12
 
8.0%
a11
 
7.3%
/11
 
7.3%
n9
 
6.0%
i8
 
5.3%
A6
 
4.0%
u5
 
3.3%
E5
 
3.3%
Other values (16)52
34.7%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing176
Missing (%)100.0%
Memory size1.5 KiB

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing175
Missing (%)99.4%
Memory size1.5 KiB
Russian Federation

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRussian Federation

Common Values

ValueCountFrequency (%)
Russian Federation1
 
0.6%
(Missing)175
99.4%

Length

2022-09-05T21:37:35.217231image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:35.294275image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
50.0%
federation1
50.0%

Most occurring characters

ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15
83.3%
Uppercase Letter2
 
11.1%
Space Separator1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s2
13.3%
i2
13.3%
a2
13.3%
n2
13.3%
e2
13.3%
u1
6.7%
d1
6.7%
r1
6.7%
t1
6.7%
o1
6.7%
Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
F1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17
94.4%
Common1
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s2
11.8%
i2
11.8%
a2
11.8%
n2
11.8%
e2
11.8%
R1
5.9%
u1
5.9%
F1
5.9%
d1
5.9%
r1
5.9%
Other values (2)2
11.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing175
Missing (%)99.4%
Memory size1.5 KiB
RU

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRU

Common Values

ValueCountFrequency (%)
RU1
 
0.6%
(Missing)175
99.4%

Length

2022-09-05T21:37:35.365396image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:35.441016image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
100.0%

Most occurring characters

ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing175
Missing (%)99.4%
Memory size1.5 KiB
Asia/Kamchatka

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
0.6%
(Missing)175
99.4%

Length

2022-09-05T21:37:35.510236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:35.585099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
100.0%

Most occurring characters

ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter11
78.6%
Uppercase Letter2
 
14.3%
Other Punctuation1
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a4
36.4%
s1
 
9.1%
i1
 
9.1%
m1
 
9.1%
c1
 
9.1%
h1
 
9.1%
t1
 
9.1%
k1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
K1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13
92.9%
Common1
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a4
30.8%
A1
 
7.7%
s1
 
7.7%
i1
 
7.7%
K1
 
7.7%
m1
 
7.7%
c1
 
7.7%
h1
 
7.7%
t1
 
7.7%
k1
 
7.7%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Interactions

2022-09-05T21:37:23.737314image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:11.750428image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.621117image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.551676image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.491751image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.432440image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.336801image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.244423image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.117926image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.014953image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.919894image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.812594image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.723073image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.806003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:11.916634image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.694081image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.622701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.564270image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.499680image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.401631image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.307455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.185047image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.087479image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.983557image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.881045image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.793677image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.890795image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:11.989487image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.766287image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.699839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.638943image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.569670image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.482045image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.379356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.257188image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.154245image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.058557image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.951595image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.871001image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.963828image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:12.936009image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.835681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.768315image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.718518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.632834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.551073image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.445426image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.325103image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.223492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.126827image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.017588image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.950071image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.038297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.004424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.909302image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.838824image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.787703image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.705352image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.622410image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.510484image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.397979image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.293173image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.193622image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.088999image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.024739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.117260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.074113image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.971658image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.902749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.855245image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.778273image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.701032image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.571619image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.463867image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.365084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.264126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.157804image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.098935image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.192948image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.143973image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.039661image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.971684image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.926848image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.841958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.768696image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.637514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.530518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.429366image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.330129image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.224965image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.174558image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.262300image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.216728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.109966image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.044016image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.996950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.906570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.832996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.706255image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.600867image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.498867image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.398370image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.297051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.251787image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.339514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.284989image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.182059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.116337image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.072476image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.980287image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.905773image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.773514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.670126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.567900image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.470862image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.367733image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.344619image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.408871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.355191image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.251719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.193124image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.150279image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.053941image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.971020image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.841328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.735884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.638895image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.542072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.440926image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.421755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.478637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.424903image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.323559image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.267263image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.220634image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.124048image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.036015image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.914381image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.803638image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.708570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.607822image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.511284image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.503397image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.576283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.487645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.402169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.336859image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.290380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.197729image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.104243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.980124image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.875657image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.779459image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.678073image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.576058image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.577307image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:24.659880image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:13.554052image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:14.478017image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:15.411909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:16.364478image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:17.271927image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:18.177300image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.048195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:19.946812image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:20.852842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:21.746092image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:22.644310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:37:23.658597image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:37:35.676679image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:37:35.931467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:37:36.165818image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:37:36.441891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:37:25.061968image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:37:25.860450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:37:26.388601image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezoneimage.mediumimage.original_embedded.show._links.nextepisode.href_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
01984016https://www.tvmaze.com/episodes/1984016/roast-battle-labelcom-1x14-14-anton-sastun#14 - Антон Шастун114.0regular2020-12-042020-12-04T00:00:00+00:0049.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198401648288https://www.tvmaze.com/shows/48288/roast-battle-labelcomRoast Battle LabelcomGame ShowRussian[Comedy]Running50.053.02019-12-24Nonehttps://www.youtube.com/playlist?list=PLmkbS48df311cZnmhlV-5q5vY0icLXdl3[Monday]NaN26NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/267/668782.jpghttps://static.tvmaze.com/uploads/images/original_untouched/267/668782.jpg<p>A bold humorous show in which comedians fight for 50,000 rubles! Six comedians will take to the stage to "fry" each other. The top two will go to the final, and only one will take the money with them!</p>1658030622https://api.tvmaze.com/shows/48288https://api.tvmaze.com/episodes/2362860NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11961003https://www.tvmaze.com/episodes/1961003/cuma-2x06-seria-12Серия 1226.0regular2020-12-042020-12-04T00:00:00+00:0021.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196100348402https://www.tvmaze.com/shows/48402/cumaЧума!ScriptedRussian[Comedy]Ended21.021.02020-05-292020-12-18https://www.ivi.ru/watch/chuma-2020[Friday]6.031NaN337.0iviNaNhttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713441.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713441.jpg<p><b>Plague</b> – a Comedy project about how hard it is to survive in the middle ages during the plague. This is a story about the residents of the fictional town of Hamburg, locked in a castle under quarantine. Also locked up in the castle is the Messenger William, who, in fact, brought the news of the plague.</p>1609468403https://api.tvmaze.com/shows/48402https://api.tvmaze.com/episodes/1961005Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21976570https://www.tvmaze.com/episodes/1976570/zakon-i-besporyadok-1x03-seria-3Серия 313.0regular2020-12-0412:002020-12-04T00:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197657052118https://www.tvmaze.com/shows/52118/zakon-i-besporyadokZakon i BesporyadokScriptedRussian[Comedy, Action, Crime]Ended30.030.02020-11-272020-12-11https://www.ivi.ru/watch/zakon-i-besporyadok12:00[Friday]NaN3NaN337.0iviNaNhttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713460.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713460.jpg<p>Lytk-Angeles, the state of Moskvachussets, has always been a quiet town where every gang had its rightful place. The Colombians smoked plantain, the Irish sipped beer, and the Chinese ate noodles. But one day the evil Russian Communists came and brought sugar with them. They slaughtered all the street vendors of plantain, seized control of the production of matryoshka dolls (a traditional Yugoslav business) and got the whole city hooked on white powder.</p><p>This will be the last case for Eustace Lynch. Famous for his lucky tattoo, an Irish gangster comes to Lytk-Angeles from Dublin (also known as Dubna) to get rid of the Communists. At the same time, Sally Raptor, a police officer from palm beach (also known as Gelendzhik) arrives in the city with a similar task.</p><p>Zakon i Besporyadok is a parody of the films of the 80s and 90s that we watched on videotapes with one-voice voice-over as a child, and a tribute to that forever-gone era when the screen belonged entirely to evil Russians, Asian martial artists and drinking detectives in ridiculous hats. Each episode parodies one of your favorite genres: the characters don't change, but they end up in an Asian fighting game, a crime Thriller, or even a neo-noir story.</p>1616037669https://api.tvmaze.com/shows/52118https://api.tvmaze.com/episodes/1976572Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31976571https://www.tvmaze.com/episodes/1976571/zakon-i-besporyadok-1x04-seria-4Серия 414.0regular2020-12-0412:002020-12-04T00:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197657152118https://www.tvmaze.com/shows/52118/zakon-i-besporyadokZakon i BesporyadokScriptedRussian[Comedy, Action, Crime]Ended30.030.02020-11-272020-12-11https://www.ivi.ru/watch/zakon-i-besporyadok12:00[Friday]NaN3NaN337.0iviNaNhttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713460.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713460.jpg<p>Lytk-Angeles, the state of Moskvachussets, has always been a quiet town where every gang had its rightful place. The Colombians smoked plantain, the Irish sipped beer, and the Chinese ate noodles. But one day the evil Russian Communists came and brought sugar with them. They slaughtered all the street vendors of plantain, seized control of the production of matryoshka dolls (a traditional Yugoslav business) and got the whole city hooked on white powder.</p><p>This will be the last case for Eustace Lynch. Famous for his lucky tattoo, an Irish gangster comes to Lytk-Angeles from Dublin (also known as Dubna) to get rid of the Communists. At the same time, Sally Raptor, a police officer from palm beach (also known as Gelendzhik) arrives in the city with a similar task.</p><p>Zakon i Besporyadok is a parody of the films of the 80s and 90s that we watched on videotapes with one-voice voice-over as a child, and a tribute to that forever-gone era when the screen belonged entirely to evil Russians, Asian martial artists and drinking detectives in ridiculous hats. Each episode parodies one of your favorite genres: the characters don't change, but they end up in an Asian fighting game, a crime Thriller, or even a neo-noir story.</p>1616037669https://api.tvmaze.com/shows/52118https://api.tvmaze.com/episodes/1976572Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41979225https://www.tvmaze.com/episodes/1979225/kotiki-1x05-seria-5Серия 515.0regular2020-12-042020-12-04T00:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197922552198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN15NaN510.0Epic MediaNaNNoneNaNNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpgNone1637555191https://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
51972557https://www.tvmaze.com/episodes/1972557/the-wolf-1x15-episode-15Episode 15115.0regular2020-12-042020-12-04T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197255747912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuNaNNoneNaNNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
61972558https://www.tvmaze.com/episodes/1972558/the-wolf-1x16-episode-16Episode 16116.0regular2020-12-042020-12-04T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197255847912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuNaNNoneNaNNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71910446https://www.tvmaze.com/episodes/1910446/the-founder-of-diabolism-q-1x20-drunkennessDrunkenness120.0regular2020-12-042020-12-04T04:00:00+00:005.0NaNNoneNaNhttps://api.tvmaze.com/episodes/191044649485https://www.tvmaze.com/shows/49485/the-founder-of-diabolism-qThe Founder of Diabolism QAnimationChinese[Comedy, Anime, History, Supernatural]Ended5.05.02020-07-312021-02-12https://v.qq.com/detail/m/mzc00200fdthd81.html[Friday]NaN56NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN386257.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675335.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675335.jpg<p>The chibi spin-off takes place during the three periods of Wei Wuxian's life (adolescence, adulthood, and rebirth after death), selecting the cute, warm, and healing parts as the main contents. This series hopes to heal the audience who loves the main story of <i>Mo Dao Zu Shi</i>, but were "injured" by the melancholy plot of the drama.</p>1621019292https://api.tvmaze.com/shows/49485https://api.tvmaze.com/episodes/1910456ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
82082172https://www.tvmaze.com/episodes/2082172/ling-jian-zun-4x29-di129ji第129集429.0regular2020-12-042020-12-04T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208217255016https://www.tvmaze.com/shows/55016/ling-jian-zunLing Jian ZunAnimationChinese[Anime]Running10.010.02019-01-15Nonehttps://v.qq.com/x/cover/2w2legt0g8z26al.html[Tuesday, Friday]NaN52NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN364730.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778535.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778535.jpg<p>The strong man was attacked and returned to his youth. He became the weakest waste young lord. He will never let go of the enemy of the previous life in this life and must make up the regret of the previous life in this life! By the time the Spirit Sword is powerful, the protagonist will be supreme in the three worlds between heaven and earth! If there is someone doesn't obey him, he will kill him with the sword!</p><p><br /> </p>1653895786https://api.tvmaze.com/shows/55016https://api.tvmaze.com/episodes/2336755ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92080222https://www.tvmaze.com/episodes/2080222/supreme-god-emperor-1x60-episode-60Episode 60160.0regular2020-12-042020-12-04T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208022255019https://www.tvmaze.com/shows/55019/supreme-god-emperorSupreme God EmperorAnimationChinese[Anime]Running10.010.02020-05-18Nonehttps://v.qq.com/detail/m/mzc00200ilydv1a.html10:00[Monday, Friday]NaN60NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN388383.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778540.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778540.jpg<p>Ten thousand years ago, Muyun's fairy King was secretly accounted for by holding a Zhuxian figure, and after a long sleep, he awakened in the famous "Muyun waste" of the southern Yun Empire in the Land of Heaven. When Muyun first woke up, he was deliberately bothered by the student Miaoxianyu. Muyun easily completed the Miaoxianyu trap, and he gave more and more alchemy skills by analogy, so the Alchemy masters outside the door could not ask for appreciation. Endless back home, Mu Yun learns that he is about to marry Nona Qin Qin Mengyao. Qin Mengyao was cold and toxic, but could not live until he was 20 years old. The marriage was only for the sake of pastoralists and family of Qin. However, under Mu Linchen's enticement, Mu Yun approves the family's issue on the condition of alchemy.</p><p><br /> </p>1653896222https://api.tvmaze.com/shows/55019https://api.tvmaze.com/episodes/2257583ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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1661995403https://www.tvmaze.com/episodes/1995403/engineering-the-future-1x02-aviationAviation12.0regular2020-12-042020-12-04T17:00:00+00:0060.0NaN<p>The way we fly is about to change, driven by a new breed of aviators not afraid to think differently. From clean, green electric aircraft to autonomous sky taxis, could the days of the jet age be numbered?</p>NaNhttps://api.tvmaze.com/episodes/199540352709https://www.tvmaze.com/shows/52709/engineering-the-futureEngineering the FutureDocumentaryEnglish[]To Be Determined60.060.02020-12-04Nonehttps://curiositystream.com/series/479/engineering-the-future[]NaN52NaN329.0HBO MaxNaNhttps://www.hbomax.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/408/1022143.jpghttps://static.tvmaze.com/uploads/images/original_untouched/408/1022143.jpg<p>An engineering revolution is underway. Driven by dedicated individuals who are building extraordinary machines that will change our lives.</p>1652630660https://api.tvmaze.com/shows/52709https://api.tvmaze.com/episodes/1995404NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1731978323https://www.tvmaze.com/episodes/1978323/zombies-2020-special-disney-holiday-magic-questDisney Holiday Magic Quest2020NaNinsignificant_special2020-12-0420:002020-12-05T01:00:00+00:0050.0NaN<p>Disney Villains have stolen the holiday magic from the Magic Kingdom Park; ZOMBIES stars race to see who can save it first.</p>NaNhttps://api.tvmaze.com/episodes/197832342077https://www.tvmaze.com/shows/42077/zombiesZOMBIESScriptedEnglish[Family, Fantasy, Music]Running120.0120.02018-02-16Nonehttps://disneynow.go.com/disney-channel-original-movies/[Friday]NaN83NaN287.0Disney+NaNhttps://www.disneyplus.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/415/1037850.jpghttps://static.tvmaze.com/uploads/images/original_untouched/415/1037850.jpg<p>As Seabrook students struggle to coexist with new students from Zombietown, an unlikely friendship between a cheerleader and a zombie could unite their community for good.</p>1657237510https://api.tvmaze.com/shows/42077https://api.tvmaze.com/episodes/2358281NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1741965175https://www.tvmaze.com/episodes/1965175/zombies-addisons-monster-mystery-1x08-feelin-the-powerFeelin' the Power18.0regular2020-12-0421:152020-12-05T02:15:00+00:003.0NaN<p>Addison must break her friends free from Vanna's hypnosis!</p>NaNhttps://api.tvmaze.com/episodes/196517551061https://www.tvmaze.com/shows/51061/zombies-addisons-monster-mysteryZOMBIES: Addison's Monster MysteryAnimationEnglish[Family, Fantasy, Music]Running3.03.02020-10-16Nonehttps://disneynow.com/shows/collection/zombies-collection/zombies-moonstone20:55[Friday]NaN41NaN83.0DisneyNOWNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/281/703168.jpghttps://static.tvmaze.com/uploads/images/original_untouched/281/703168.jpg<p>Your favorite Seabrook monsters are back with all new mysteries no one saw coming. The story begins at Seabrook High, where zombies, werewolves, and humans are all co-existing happily. A new girl at school, Vanna, whom Addison immediately befriends, threatens to shake up the dynamic when they learn that she is not all that she seems.</p>1657252825https://api.tvmaze.com/shows/51061https://api.tvmaze.com/episodes/2166724United StatesUSAmerica/New_Yorkhttps://static.tvmaze.com/uploads/images/medium_landscape/286/717414.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/717414.jpgNaN78.0Disney ChannelUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaN
1751951739https://www.tvmaze.com/episodes/1951739/205-live-2020-12-04-205-live-210205 Live #210202049.0regular2020-12-0422:002020-12-05T03:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/195173922536https://www.tvmaze.com/shows/22536/205-live205 LiveSportsEnglish[]Ended60.060.02016-11-292022-02-11https://www.wwe.com/shows/wwe-205-live22:00[Friday]NaN82NaN15.0WWE NetworkNaNNoneNaNNaN323420.0tt6286394https://static.tvmaze.com/uploads/images/medium_portrait/96/240881.jpghttps://static.tvmaze.com/uploads/images/original_untouched/96/240881.jpg<p><i>WWE 205 Live</i>, also simply called <b>205 Live</b>, is a live professional wrestling WWE Network series produced by WWE, which exclusively features the promotion's cruiserweight division, wherein all participants are billed at a weight of 205 lbs. or less.</p><p>The final episode of the series aired on February 11, 2022. On February 18, it was replaced by <i>WWE NXT: Level Up</i>.</p>1649921818https://api.tvmaze.com/shows/22536https://api.tvmaze.com/episodes/2267545United StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN